diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/AnalyticTensorAlgebra.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/AnalyticTensorAlgebra.kt
index 5c92c56c4..cd13e0752 100644
--- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/AnalyticTensorAlgebra.kt
+++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/AnalyticTensorAlgebra.kt
@@ -6,7 +6,7 @@
 package space.kscience.kmath.tensors.api
 
 /**
- * Element-wise analytic operations on [TensorStructure].
+ * Element-wise analytic operations on [Tensor].
  *
  * @param T the type of items closed under analytic functions in the tensors.
  */
@@ -14,54 +14,54 @@ public interface AnalyticTensorAlgebra<T> :
     TensorPartialDivisionAlgebra<T> {
 
     //For information: https://pytorch.org/docs/stable/generated/torch.exp.html
-    public fun TensorStructure<T>.exp(): TensorStructure<T>
+    public fun Tensor<T>.exp(): Tensor<T>
 
     //For information: https://pytorch.org/docs/stable/generated/torch.log.html
-    public fun TensorStructure<T>.log(): TensorStructure<T>
+    public fun Tensor<T>.log(): Tensor<T>
 
     //For information: https://pytorch.org/docs/stable/generated/torch.sqrt.html
-    public fun TensorStructure<T>.sqrt(): TensorStructure<T>
+    public fun Tensor<T>.sqrt(): Tensor<T>
 
     //For information: https://pytorch.org/docs/stable/generated/torch.acos.html#torch.cos
-    public fun TensorStructure<T>.cos(): TensorStructure<T>
+    public fun Tensor<T>.cos(): Tensor<T>
 
     //For information: https://pytorch.org/docs/stable/generated/torch.acos.html#torch.acos
-    public fun TensorStructure<T>.acos(): TensorStructure<T>
+    public fun Tensor<T>.acos(): Tensor<T>
 
     //For information: https://pytorch.org/docs/stable/generated/torch.acosh.html#torch.cosh
-    public fun TensorStructure<T>.cosh(): TensorStructure<T>
+    public fun Tensor<T>.cosh(): Tensor<T>
 
     //For information: https://pytorch.org/docs/stable/generated/torch.acosh.html#torch.acosh
-    public fun TensorStructure<T>.acosh(): TensorStructure<T>
+    public fun Tensor<T>.acosh(): Tensor<T>
 
     //For information: https://pytorch.org/docs/stable/generated/torch.asin.html#torch.sin
-    public fun TensorStructure<T>.sin(): TensorStructure<T>
+    public fun Tensor<T>.sin(): Tensor<T>
 
     //For information: https://pytorch.org/docs/stable/generated/torch.asin.html#torch.asin
-    public fun TensorStructure<T>.asin(): TensorStructure<T>
+    public fun Tensor<T>.asin(): Tensor<T>
 
     //For information: https://pytorch.org/docs/stable/generated/torch.asin.html#torch.sinh
-    public fun TensorStructure<T>.sinh(): TensorStructure<T>
+    public fun Tensor<T>.sinh(): Tensor<T>
 
     //For information: https://pytorch.org/docs/stable/generated/torch.asin.html#torch.asinh
-    public fun TensorStructure<T>.asinh(): TensorStructure<T>
+    public fun Tensor<T>.asinh(): Tensor<T>
 
     //For information: https://pytorch.org/docs/stable/generated/torch.atan.html#torch.tan
-    public fun TensorStructure<T>.tan(): TensorStructure<T>
+    public fun Tensor<T>.tan(): Tensor<T>
 
     //https://pytorch.org/docs/stable/generated/torch.atan.html#torch.atan
-    public fun TensorStructure<T>.atan(): TensorStructure<T>
+    public fun Tensor<T>.atan(): Tensor<T>
 
     //For information: https://pytorch.org/docs/stable/generated/torch.atanh.html#torch.tanh
-    public fun TensorStructure<T>.tanh(): TensorStructure<T>
+    public fun Tensor<T>.tanh(): Tensor<T>
 
     //For information: https://pytorch.org/docs/stable/generated/torch.atanh.html#torch.atanh
-    public fun TensorStructure<T>.atanh(): TensorStructure<T>
+    public fun Tensor<T>.atanh(): Tensor<T>
 
     //For information: https://pytorch.org/docs/stable/generated/torch.ceil.html#torch.ceil
-    public fun TensorStructure<T>.ceil(): TensorStructure<T>
+    public fun Tensor<T>.ceil(): Tensor<T>
 
     //For information: https://pytorch.org/docs/stable/generated/torch.floor.html#torch.floor
-    public fun TensorStructure<T>.floor(): TensorStructure<T>
+    public fun Tensor<T>.floor(): Tensor<T>
 
 }
\ No newline at end of file
diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/LinearOpsTensorAlgebra.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/LinearOpsTensorAlgebra.kt
index bcbb52a1b..527e5d386 100644
--- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/LinearOpsTensorAlgebra.kt
+++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/LinearOpsTensorAlgebra.kt
@@ -6,7 +6,7 @@
 package space.kscience.kmath.tensors.api
 
 /**
- * Common linear algebra operations. Operates on [TensorStructure].
+ * Common linear algebra operations. Operates on [Tensor].
  *
  * @param T the type of items closed under division in the tensors.
  */
@@ -19,7 +19,7 @@ public interface LinearOpsTensorAlgebra<T> :
      *
      * @return the determinant.
      */
-    public fun TensorStructure<T>.det(): TensorStructure<T>
+    public fun Tensor<T>.det(): Tensor<T>
 
     /**
      * Computes the multiplicative inverse matrix of a square matrix input, or of each square matrix in a batched input.
@@ -29,7 +29,7 @@ public interface LinearOpsTensorAlgebra<T> :
      *
      * @return the multiplicative inverse of a matrix.
      */
-    public fun TensorStructure<T>.inv(): TensorStructure<T>
+    public fun Tensor<T>.inv(): Tensor<T>
 
     /**
      * Cholesky decomposition.
@@ -44,7 +44,7 @@ public interface LinearOpsTensorAlgebra<T> :
      *
      * @return the batch of L matrices.
      */
-    public fun TensorStructure<T>.cholesky(): TensorStructure<T>
+    public fun Tensor<T>.cholesky(): Tensor<T>
 
     /**
      * QR decomposition.
@@ -57,7 +57,7 @@ public interface LinearOpsTensorAlgebra<T> :
      *
      * @return pair of Q and R tensors.
      */
-    public fun TensorStructure<T>.qr(): Pair<TensorStructure<T>, TensorStructure<T>>
+    public fun Tensor<T>.qr(): Pair<Tensor<T>, Tensor<T>>
 
     /**
      * LUP decomposition
@@ -70,7 +70,7 @@ public interface LinearOpsTensorAlgebra<T> :
      *
      * * @return triple of P, L and U tensors
      */
-    public fun TensorStructure<T>.lu(): Triple<TensorStructure<T>, TensorStructure<T>, TensorStructure<T>>
+    public fun Tensor<T>.lu(): Triple<Tensor<T>, Tensor<T>, Tensor<T>>
 
     /**
      * Singular Value Decomposition.
@@ -83,7 +83,7 @@ public interface LinearOpsTensorAlgebra<T> :
      *
      * @return the determinant.
      */
-    public fun TensorStructure<T>.svd(): Triple<TensorStructure<T>, TensorStructure<T>, TensorStructure<T>>
+    public fun Tensor<T>.svd(): Triple<Tensor<T>, Tensor<T>, Tensor<T>>
 
     /**
      * Returns eigenvalues and eigenvectors of a real symmetric matrix input or a batch of real symmetric matrices,
@@ -92,6 +92,6 @@ public interface LinearOpsTensorAlgebra<T> :
      *
      * @return a pair (eigenvalues, eigenvectors)
      */
-    public fun TensorStructure<T>.symEig(): Pair<TensorStructure<T>, TensorStructure<T>>
+    public fun Tensor<T>.symEig(): Pair<Tensor<T>, Tensor<T>>
 
 }
\ No newline at end of file
diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorStructure.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/Tensor.kt
similarity index 60%
rename from kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorStructure.kt
rename to kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/Tensor.kt
index edecd6383..179787684 100644
--- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorStructure.kt
+++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/Tensor.kt
@@ -2,4 +2,4 @@ package space.kscience.kmath.tensors.api
 
 import space.kscience.kmath.nd.MutableStructureND
 
-public typealias TensorStructure<T> = MutableStructureND<T>
+public typealias Tensor<T> = MutableStructureND<T>
diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorAlgebra.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorAlgebra.kt
index 96d6985d8..b9c707c0b 100644
--- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorAlgebra.kt
+++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorAlgebra.kt
@@ -8,19 +8,19 @@ package space.kscience.kmath.tensors.api
 import space.kscience.kmath.operations.Algebra
 
 /**
- * Algebra over a ring on [TensorStructure].
+ * Algebra over a ring on [Tensor].
  * For more information: https://proofwiki.org/wiki/Definition:Algebra_over_Ring
  *
  * @param T the type of items in the tensors.
  */
-public interface TensorAlgebra<T>: Algebra<TensorStructure<T>> {
+public interface TensorAlgebra<T>: Algebra<Tensor<T>> {
 
     /**
      * Returns a single tensor value of unit dimension. The tensor shape must be equal to [1].
      *
      * @return the value of a scalar tensor.
      */
-    public fun TensorStructure<T>.value(): T
+    public fun Tensor<T>.value(): T
 
     /**
      * Each element of the tensor [other] is added to this value.
@@ -29,7 +29,7 @@ public interface TensorAlgebra<T>: Algebra<TensorStructure<T>> {
      * @param other tensor to be added.
      * @return the sum of this value and tensor [other].
      */
-    public operator fun T.plus(other: TensorStructure<T>): TensorStructure<T>
+    public operator fun T.plus(other: Tensor<T>): Tensor<T>
 
     /**
      * Adds the scalar [value] to each element of this tensor and returns a new resulting tensor.
@@ -37,7 +37,7 @@ public interface TensorAlgebra<T>: Algebra<TensorStructure<T>> {
      * @param value the number to be added to each element of this tensor.
      * @return the sum of this tensor and [value].
      */
-    public operator fun TensorStructure<T>.plus(value: T): TensorStructure<T>
+    public operator fun Tensor<T>.plus(value: T): Tensor<T>
 
     /**
      * Each element of the tensor [other] is added to each element of this tensor.
@@ -46,21 +46,21 @@ public interface TensorAlgebra<T>: Algebra<TensorStructure<T>> {
      * @param other tensor to be added.
      * @return the sum of this tensor and [other].
      */
-    public operator fun TensorStructure<T>.plus(other: TensorStructure<T>): TensorStructure<T>
+    public operator fun Tensor<T>.plus(other: Tensor<T>): Tensor<T>
 
     /**
      * Adds the scalar [value] to each element of this tensor.
      *
      * @param value the number to be added to each element of this tensor.
      */
-    public operator fun TensorStructure<T>.plusAssign(value: T): Unit
+    public operator fun Tensor<T>.plusAssign(value: T): Unit
 
     /**
      * Each element of the tensor [other] is added to each element of this tensor.
      *
      * @param other tensor to be added.
      */
-    public operator fun TensorStructure<T>.plusAssign(other: TensorStructure<T>): Unit
+    public operator fun Tensor<T>.plusAssign(other: Tensor<T>): Unit
 
 
     /**
@@ -70,7 +70,7 @@ public interface TensorAlgebra<T>: Algebra<TensorStructure<T>> {
      * @param other tensor to be subtracted.
      * @return the difference between this value and tensor [other].
      */
-    public operator fun T.minus(other: TensorStructure<T>): TensorStructure<T>
+    public operator fun T.minus(other: Tensor<T>): Tensor<T>
 
     /**
      * Subtracts the scalar [value] from each element of this tensor and returns a new resulting tensor.
@@ -78,7 +78,7 @@ public interface TensorAlgebra<T>: Algebra<TensorStructure<T>> {
      * @param value the number to be subtracted from each element of this tensor.
      * @return the difference between this tensor and [value].
      */
-    public operator fun TensorStructure<T>.minus(value: T): TensorStructure<T>
+    public operator fun Tensor<T>.minus(value: T): Tensor<T>
 
     /**
      * Each element of the tensor [other] is subtracted from each element of this tensor.
@@ -87,21 +87,21 @@ public interface TensorAlgebra<T>: Algebra<TensorStructure<T>> {
      * @param other tensor to be subtracted.
      * @return the difference between this tensor and [other].
      */
-    public operator fun TensorStructure<T>.minus(other: TensorStructure<T>): TensorStructure<T>
+    public operator fun Tensor<T>.minus(other: Tensor<T>): Tensor<T>
 
     /**
      * Subtracts the scalar [value] from each element of this tensor.
      *
      * @param value the number to be subtracted from each element of this tensor.
      */
-    public operator fun TensorStructure<T>.minusAssign(value: T): Unit
+    public operator fun Tensor<T>.minusAssign(value: T): Unit
 
     /**
      * Each element of the tensor [other] is subtracted from each element of this tensor.
      *
      * @param other tensor to be subtracted.
      */
-    public operator fun TensorStructure<T>.minusAssign(other: TensorStructure<T>): Unit
+    public operator fun Tensor<T>.minusAssign(other: Tensor<T>): Unit
 
 
     /**
@@ -111,7 +111,7 @@ public interface TensorAlgebra<T>: Algebra<TensorStructure<T>> {
      * @param other tensor to be multiplied.
      * @return the product of this value and tensor [other].
      */
-    public operator fun T.times(other: TensorStructure<T>): TensorStructure<T>
+    public operator fun T.times(other: Tensor<T>): Tensor<T>
 
     /**
      * Multiplies the scalar [value] by each element of this tensor and returns a new resulting tensor.
@@ -119,7 +119,7 @@ public interface TensorAlgebra<T>: Algebra<TensorStructure<T>> {
      * @param value the number to be multiplied by each element of this tensor.
      * @return the product of this tensor and [value].
      */
-    public operator fun TensorStructure<T>.times(value: T): TensorStructure<T>
+    public operator fun Tensor<T>.times(value: T): Tensor<T>
 
     /**
      * Each element of the tensor [other] is multiplied by each element of this tensor.
@@ -128,28 +128,28 @@ public interface TensorAlgebra<T>: Algebra<TensorStructure<T>> {
      * @param other tensor to be multiplied.
      * @return the product of this tensor and [other].
      */
-    public operator fun TensorStructure<T>.times(other: TensorStructure<T>): TensorStructure<T>
+    public operator fun Tensor<T>.times(other: Tensor<T>): Tensor<T>
 
     /**
      * Multiplies the scalar [value] by each element of this tensor.
      *
      * @param value the number to be multiplied by each element of this tensor.
      */
-    public operator fun TensorStructure<T>.timesAssign(value: T): Unit
+    public operator fun Tensor<T>.timesAssign(value: T): Unit
 
     /**
      * Each element of the tensor [other] is multiplied by each element of this tensor.
      *
      * @param other tensor to be multiplied.
      */
-    public operator fun TensorStructure<T>.timesAssign(other: TensorStructure<T>): Unit
+    public operator fun Tensor<T>.timesAssign(other: Tensor<T>): Unit
 
     /**
      * Numerical negative, element-wise.
      *
      * @return tensor negation of the original tensor.
      */
-    public operator fun TensorStructure<T>.unaryMinus(): TensorStructure<T>
+    public operator fun Tensor<T>.unaryMinus(): Tensor<T>
 
     /**
      * Returns the tensor at index i
@@ -158,7 +158,7 @@ public interface TensorAlgebra<T>: Algebra<TensorStructure<T>> {
      * @param i index of the extractable tensor
      * @return subtensor of the original tensor with index [i]
      */
-    public operator fun TensorStructure<T>.get(i: Int): TensorStructure<T>
+    public operator fun Tensor<T>.get(i: Int): Tensor<T>
 
     /**
      * Returns a tensor that is a transposed version of this tensor. The given dimensions [i] and [j] are swapped.
@@ -168,7 +168,7 @@ public interface TensorAlgebra<T>: Algebra<TensorStructure<T>> {
      * @param j the second dimension to be transposed
      * @return transposed tensor
      */
-    public fun TensorStructure<T>.transpose(i: Int = -2, j: Int = -1): TensorStructure<T>
+    public fun Tensor<T>.transpose(i: Int = -2, j: Int = -1): Tensor<T>
 
     /**
      * Returns a new tensor with the same data as the self tensor but of a different shape.
@@ -178,7 +178,7 @@ public interface TensorAlgebra<T>: Algebra<TensorStructure<T>> {
      * @param shape the desired size
      * @return tensor with new shape
      */
-    public fun TensorStructure<T>.view(shape: IntArray): TensorStructure<T>
+    public fun Tensor<T>.view(shape: IntArray): Tensor<T>
 
     /**
      * View this tensor as the same size as [other].
@@ -188,7 +188,7 @@ public interface TensorAlgebra<T>: Algebra<TensorStructure<T>> {
      * @param other the result tensor has the same size as other.
      * @return the result tensor with the same size as other.
      */
-    public fun TensorStructure<T>.viewAs(other: TensorStructure<T>): TensorStructure<T>
+    public fun Tensor<T>.viewAs(other: Tensor<T>): Tensor<T>
 
     /**
      * Matrix product of two tensors.
@@ -219,7 +219,7 @@ public interface TensorAlgebra<T>: Algebra<TensorStructure<T>> {
      * @param other tensor to be multiplied
      * @return mathematical product of two tensors
      */
-    public infix fun TensorStructure<T>.dot(other: TensorStructure<T>): TensorStructure<T>
+    public infix fun Tensor<T>.dot(other: Tensor<T>): Tensor<T>
 
     /**
      * Creates a tensor whose diagonals of certain 2D planes (specified by [dim1] and [dim2])
@@ -245,10 +245,10 @@ public interface TensorAlgebra<T>: Algebra<TensorStructure<T>> {
      * are filled by [diagonalEntries]
      */
     public fun diagonalEmbedding(
-        diagonalEntries: TensorStructure<T>,
+        diagonalEntries: Tensor<T>,
         offset: Int = 0,
         dim1: Int = -2,
         dim2: Int = -1
-    ): TensorStructure<T>
+    ): Tensor<T>
 
 }
diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorPartialDivisionAlgebra.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorPartialDivisionAlgebra.kt
index eccc6fa0d..921157963 100644
--- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorPartialDivisionAlgebra.kt
+++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/api/TensorPartialDivisionAlgebra.kt
@@ -6,7 +6,7 @@
 package space.kscience.kmath.tensors.api
 
 /**
- * Algebra over a field with partial division on [TensorStructure].
+ * Algebra over a field with partial division on [Tensor].
  * For more information: https://proofwiki.org/wiki/Definition:Division_Algebra
  *
  * @param T the type of items closed under division in the tensors.
@@ -21,7 +21,7 @@ public interface TensorPartialDivisionAlgebra<T> :
      * @param other tensor to divide by.
      * @return the division of this value by the tensor [other].
      */
-    public operator fun T.div(other: TensorStructure<T>): TensorStructure<T>
+    public operator fun T.div(other: Tensor<T>): Tensor<T>
 
     /**
      * Divide by the scalar [value] each element of this tensor returns a new resulting tensor.
@@ -29,7 +29,7 @@ public interface TensorPartialDivisionAlgebra<T> :
      * @param value the number to divide by each element of this tensor.
      * @return the division of this tensor by the [value].
      */
-    public operator fun TensorStructure<T>.div(value: T): TensorStructure<T>
+    public operator fun Tensor<T>.div(value: T): Tensor<T>
 
     /**
      * Each element of the tensor [other] is divided by each element of this tensor.
@@ -38,19 +38,19 @@ public interface TensorPartialDivisionAlgebra<T> :
      * @param other tensor to be divided by.
      * @return the division of this tensor by [other].
      */
-    public operator fun TensorStructure<T>.div(other: TensorStructure<T>): TensorStructure<T>
+    public operator fun Tensor<T>.div(other: Tensor<T>): Tensor<T>
 
     /**
      * Divides by the scalar [value] each element of this tensor.
      *
      * @param value the number to divide by each element of this tensor.
      */
-    public operator fun TensorStructure<T>.divAssign(value: T)
+    public operator fun Tensor<T>.divAssign(value: T)
 
     /**
      * Each element of this tensor is divided by each element of the [other] tensor.
      *
      * @param other tensor to be divide by.
      */
-    public operator fun TensorStructure<T>.divAssign(other: TensorStructure<T>)
+    public operator fun Tensor<T>.divAssign(other: Tensor<T>)
 }
diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/BufferedTensor.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/BufferedTensor.kt
index 9541a97f9..d0882efb8 100644
--- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/BufferedTensor.kt
+++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/BufferedTensor.kt
@@ -2,7 +2,7 @@ package space.kscience.kmath.tensors.core
 
 import space.kscience.kmath.nd.MutableBufferND
 import space.kscience.kmath.structures.*
-import space.kscience.kmath.tensors.api.TensorStructure
+import space.kscience.kmath.tensors.api.Tensor
 import space.kscience.kmath.tensors.core.algebras.TensorLinearStructure
 
 
@@ -10,7 +10,7 @@ public open class BufferedTensor<T>(
     override val shape: IntArray,
     internal val mutableBuffer: MutableBuffer<T>,
     internal val bufferStart: Int
-) : TensorStructure<T> {
+) : Tensor<T> {
     public val linearStructure: TensorLinearStructure
         get() = TensorLinearStructure(shape)
 
@@ -53,33 +53,33 @@ internal fun BufferedTensor<Int>.asTensor(): IntTensor =
 internal fun BufferedTensor<Double>.asTensor(): DoubleTensor =
     DoubleTensor(this.shape, this.mutableBuffer.array(), this.bufferStart)
 
-internal fun <T> TensorStructure<T>.copyToBufferedTensor(): BufferedTensor<T> =
+internal fun <T> Tensor<T>.copyToBufferedTensor(): BufferedTensor<T> =
     BufferedTensor(
         this.shape,
         TensorLinearStructure(this.shape).indices().map(this::get).toMutableList().asMutableBuffer(), 0
     )
 
-internal fun <T> TensorStructure<T>.toBufferedTensor(): BufferedTensor<T> = when (this) {
+internal fun <T> Tensor<T>.toBufferedTensor(): BufferedTensor<T> = when (this) {
     is BufferedTensor<T> -> this
     is MutableBufferND<T> -> if (this.strides.strides contentEquals TensorLinearStructure(this.shape).strides)
         BufferedTensor(this.shape, this.mutableBuffer, 0) else this.copyToBufferedTensor()
     else -> this.copyToBufferedTensor()
 }
 
-internal val TensorStructure<Double>.tensor: DoubleTensor
+internal val Tensor<Double>.tensor: DoubleTensor
     get() = when (this) {
         is DoubleTensor -> this
         else -> this.toBufferedTensor().asTensor()
     }
 
-internal val TensorStructure<Int>.tensor: IntTensor
+internal val Tensor<Int>.tensor: IntTensor
     get() = when (this) {
         is IntTensor -> this
         else -> this.toBufferedTensor().asTensor()
     }
 
-public fun TensorStructure<Double>.toDoubleTensor(): DoubleTensor = this.tensor
-public fun TensorStructure<Int>.toIntTensor(): IntTensor = this.tensor
+public fun Tensor<Double>.toDoubleTensor(): DoubleTensor = this.tensor
+public fun Tensor<Int>.toIntTensor(): IntTensor = this.tensor
 
 public fun Array<DoubleArray>.toDoubleTensor(): DoubleTensor {
     val n = size
diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/BroadcastDoubleTensorAlgebra.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/BroadcastDoubleTensorAlgebra.kt
index 9b97d5ef2..873ec9027 100644
--- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/BroadcastDoubleTensorAlgebra.kt
+++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/BroadcastDoubleTensorAlgebra.kt
@@ -5,7 +5,7 @@
 
 package space.kscience.kmath.tensors.core.algebras
 
-import space.kscience.kmath.tensors.api.TensorStructure
+import space.kscience.kmath.tensors.api.Tensor
 import space.kscience.kmath.tensors.core.*
 import space.kscience.kmath.tensors.core.broadcastTensors
 import space.kscience.kmath.tensors.core.broadcastTo
@@ -16,7 +16,7 @@ import space.kscience.kmath.tensors.core.broadcastTo
  */
 public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
 
-    override fun TensorStructure<Double>.plus(other: TensorStructure<Double>): DoubleTensor {
+    override fun Tensor<Double>.plus(other: Tensor<Double>): DoubleTensor {
         val broadcast = broadcastTensors(tensor, other.tensor)
         val newThis = broadcast[0]
         val newOther = broadcast[1]
@@ -26,7 +26,7 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
         return DoubleTensor(newThis.shape, resBuffer)
     }
 
-    override fun TensorStructure<Double>.plusAssign(other: TensorStructure<Double>) {
+    override fun Tensor<Double>.plusAssign(other: Tensor<Double>) {
         val newOther = broadcastTo(other.tensor, tensor.shape)
         for (i in 0 until tensor.linearStructure.linearSize) {
             tensor.mutableBuffer.array()[tensor.bufferStart + i] +=
@@ -34,7 +34,7 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
         }
     }
 
-    override fun TensorStructure<Double>.minus(other: TensorStructure<Double>): DoubleTensor {
+    override fun Tensor<Double>.minus(other: Tensor<Double>): DoubleTensor {
         val broadcast = broadcastTensors(tensor, other.tensor)
         val newThis = broadcast[0]
         val newOther = broadcast[1]
@@ -44,7 +44,7 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
         return DoubleTensor(newThis.shape, resBuffer)
     }
 
-    override fun TensorStructure<Double>.minusAssign(other: TensorStructure<Double>) {
+    override fun Tensor<Double>.minusAssign(other: Tensor<Double>) {
         val newOther = broadcastTo(other.tensor, tensor.shape)
         for (i in 0 until tensor.linearStructure.linearSize) {
             tensor.mutableBuffer.array()[tensor.bufferStart + i] -=
@@ -52,7 +52,7 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
         }
     }
 
-    override fun TensorStructure<Double>.times(other: TensorStructure<Double>): DoubleTensor {
+    override fun Tensor<Double>.times(other: Tensor<Double>): DoubleTensor {
         val broadcast = broadcastTensors(tensor, other.tensor)
         val newThis = broadcast[0]
         val newOther = broadcast[1]
@@ -63,7 +63,7 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
         return DoubleTensor(newThis.shape, resBuffer)
     }
 
-    override fun TensorStructure<Double>.timesAssign(other: TensorStructure<Double>) {
+    override fun Tensor<Double>.timesAssign(other: Tensor<Double>) {
         val newOther = broadcastTo(other.tensor, tensor.shape)
         for (i in 0 until tensor.linearStructure.linearSize) {
             tensor.mutableBuffer.array()[tensor.bufferStart + i] *=
@@ -71,7 +71,7 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
         }
     }
 
-    override fun TensorStructure<Double>.div(other: TensorStructure<Double>): DoubleTensor {
+    override fun Tensor<Double>.div(other: Tensor<Double>): DoubleTensor {
         val broadcast = broadcastTensors(tensor, other.tensor)
         val newThis = broadcast[0]
         val newOther = broadcast[1]
@@ -82,7 +82,7 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
         return DoubleTensor(newThis.shape, resBuffer)
     }
 
-    override fun TensorStructure<Double>.divAssign(other: TensorStructure<Double>) {
+    override fun Tensor<Double>.divAssign(other: Tensor<Double>) {
         val newOther = broadcastTo(other.tensor, tensor.shape)
         for (i in 0 until tensor.linearStructure.linearSize) {
             tensor.mutableBuffer.array()[tensor.bufferStart + i] /=
diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/DoubleAnalyticTensorAlgebra.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/DoubleAnalyticTensorAlgebra.kt
index 4a942df84..9aa6f093e 100644
--- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/DoubleAnalyticTensorAlgebra.kt
+++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/DoubleAnalyticTensorAlgebra.kt
@@ -6,7 +6,7 @@
 package space.kscience.kmath.tensors.core.algebras
 
 import space.kscience.kmath.tensors.api.AnalyticTensorAlgebra
-import space.kscience.kmath.tensors.api.TensorStructure
+import space.kscience.kmath.tensors.api.Tensor
 import space.kscience.kmath.tensors.core.DoubleTensor
 import space.kscience.kmath.tensors.core.tensor
 import kotlin.math.*
@@ -14,38 +14,38 @@ import kotlin.math.*
 public object DoubleAnalyticTensorAlgebra :
     AnalyticTensorAlgebra<Double>,
     DoubleTensorAlgebra() {
-    override fun TensorStructure<Double>.exp(): DoubleTensor = tensor.map(::exp)
+    override fun Tensor<Double>.exp(): DoubleTensor = tensor.map(::exp)
 
-    override fun TensorStructure<Double>.log(): DoubleTensor = tensor.map(::ln)
+    override fun Tensor<Double>.log(): DoubleTensor = tensor.map(::ln)
 
-    override fun TensorStructure<Double>.sqrt(): DoubleTensor = tensor.map(::sqrt)
+    override fun Tensor<Double>.sqrt(): DoubleTensor = tensor.map(::sqrt)
 
-    override fun TensorStructure<Double>.cos(): DoubleTensor = tensor.map(::cos)
+    override fun Tensor<Double>.cos(): DoubleTensor = tensor.map(::cos)
 
-    override fun TensorStructure<Double>.acos(): DoubleTensor = tensor.map(::acos)
+    override fun Tensor<Double>.acos(): DoubleTensor = tensor.map(::acos)
 
-    override fun TensorStructure<Double>.cosh(): DoubleTensor = tensor.map(::cosh)
+    override fun Tensor<Double>.cosh(): DoubleTensor = tensor.map(::cosh)
 
-    override fun TensorStructure<Double>.acosh(): DoubleTensor = tensor.map(::acosh)
+    override fun Tensor<Double>.acosh(): DoubleTensor = tensor.map(::acosh)
 
-    override fun TensorStructure<Double>.sin(): DoubleTensor = tensor.map(::sin)
+    override fun Tensor<Double>.sin(): DoubleTensor = tensor.map(::sin)
 
-    override fun TensorStructure<Double>.asin(): DoubleTensor = tensor.map(::asin)
+    override fun Tensor<Double>.asin(): DoubleTensor = tensor.map(::asin)
 
-    override fun TensorStructure<Double>.sinh(): DoubleTensor = tensor.map(::sinh)
+    override fun Tensor<Double>.sinh(): DoubleTensor = tensor.map(::sinh)
 
-    override fun TensorStructure<Double>.asinh(): DoubleTensor = tensor.map(::asinh)
+    override fun Tensor<Double>.asinh(): DoubleTensor = tensor.map(::asinh)
 
-    override fun TensorStructure<Double>.tan(): DoubleTensor = tensor.map(::tan)
+    override fun Tensor<Double>.tan(): DoubleTensor = tensor.map(::tan)
 
-    override fun TensorStructure<Double>.atan(): DoubleTensor = tensor.map(::atan)
+    override fun Tensor<Double>.atan(): DoubleTensor = tensor.map(::atan)
 
-    override fun TensorStructure<Double>.tanh(): DoubleTensor = tensor.map(::tanh)
+    override fun Tensor<Double>.tanh(): DoubleTensor = tensor.map(::tanh)
 
-    override fun TensorStructure<Double>.atanh(): DoubleTensor = tensor.map(::atanh)
+    override fun Tensor<Double>.atanh(): DoubleTensor = tensor.map(::atanh)
 
-    override fun TensorStructure<Double>.ceil(): DoubleTensor = tensor.map(::ceil)
+    override fun Tensor<Double>.ceil(): DoubleTensor = tensor.map(::ceil)
 
-    override fun TensorStructure<Double>.floor(): DoubleTensor = tensor.map(::floor)
+    override fun Tensor<Double>.floor(): DoubleTensor = tensor.map(::floor)
 
 }
\ No newline at end of file
diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/DoubleLinearOpsTensorAlgebra.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/DoubleLinearOpsTensorAlgebra.kt
index dd5ad5a61..89345e315 100644
--- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/DoubleLinearOpsTensorAlgebra.kt
+++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/DoubleLinearOpsTensorAlgebra.kt
@@ -8,7 +8,7 @@ package space.kscience.kmath.tensors.core.algebras
 import space.kscience.kmath.tensors.api.LinearOpsTensorAlgebra
 import space.kscience.kmath.nd.as1D
 import space.kscience.kmath.nd.as2D
-import space.kscience.kmath.tensors.api.TensorStructure
+import space.kscience.kmath.tensors.api.Tensor
 import space.kscience.kmath.tensors.core.*
 import space.kscience.kmath.tensors.core.checkSquareMatrix
 import space.kscience.kmath.tensors.core.choleskyHelper
@@ -25,19 +25,19 @@ public object DoubleLinearOpsTensorAlgebra :
     LinearOpsTensorAlgebra<Double>,
     DoubleTensorAlgebra() {
 
-    override fun TensorStructure<Double>.inv(): DoubleTensor = invLU(1e-9)
+    override fun Tensor<Double>.inv(): DoubleTensor = invLU(1e-9)
 
-    override fun TensorStructure<Double>.det(): DoubleTensor = detLU(1e-9)
+    override fun Tensor<Double>.det(): DoubleTensor = detLU(1e-9)
 
-    public fun TensorStructure<Double>.luFactor(epsilon: Double): Pair<DoubleTensor, IntTensor> =
+    public fun Tensor<Double>.luFactor(epsilon: Double): Pair<DoubleTensor, IntTensor> =
         computeLU(tensor, epsilon)
             ?: throw IllegalArgumentException("Tensor contains matrices which are singular at precision $epsilon")
 
-    public fun TensorStructure<Double>.luFactor(): Pair<DoubleTensor, IntTensor> = luFactor(1e-9)
+    public fun Tensor<Double>.luFactor(): Pair<DoubleTensor, IntTensor> = luFactor(1e-9)
 
     public fun luPivot(
-        luTensor: TensorStructure<Double>,
-        pivotsTensor: TensorStructure<Int>
+        luTensor: Tensor<Double>,
+        pivotsTensor: Tensor<Int>
     ): Triple<DoubleTensor, DoubleTensor, DoubleTensor> {
         checkSquareMatrix(luTensor.shape)
         check(
@@ -66,7 +66,7 @@ public object DoubleLinearOpsTensorAlgebra :
         return Triple(pTensor, lTensor, uTensor)
     }
 
-    public fun TensorStructure<Double>.cholesky(epsilon: Double): DoubleTensor {
+    public fun Tensor<Double>.cholesky(epsilon: Double): DoubleTensor {
         checkSquareMatrix(shape)
         checkPositiveDefinite(tensor, epsilon)
 
@@ -79,9 +79,9 @@ public object DoubleLinearOpsTensorAlgebra :
         return lTensor
     }
 
-    override fun TensorStructure<Double>.cholesky(): DoubleTensor = cholesky(1e-6)
+    override fun Tensor<Double>.cholesky(): DoubleTensor = cholesky(1e-6)
 
-    override fun TensorStructure<Double>.qr(): Pair<DoubleTensor, DoubleTensor> {
+    override fun Tensor<Double>.qr(): Pair<DoubleTensor, DoubleTensor> {
         checkSquareMatrix(shape)
         val qTensor = zeroesLike()
         val rTensor = zeroesLike()
@@ -95,10 +95,10 @@ public object DoubleLinearOpsTensorAlgebra :
         return qTensor to rTensor
     }
 
-    override fun TensorStructure<Double>.svd(): Triple<DoubleTensor, DoubleTensor, DoubleTensor> =
+    override fun Tensor<Double>.svd(): Triple<DoubleTensor, DoubleTensor, DoubleTensor> =
         svd(epsilon = 1e-10)
 
-    public fun TensorStructure<Double>.svd(epsilon: Double): Triple<DoubleTensor, DoubleTensor, DoubleTensor> {
+    public fun Tensor<Double>.svd(epsilon: Double): Triple<DoubleTensor, DoubleTensor, DoubleTensor> {
         val size = tensor.linearStructure.dim
         val commonShape = tensor.shape.sliceArray(0 until size - 2)
         val (n, m) = tensor.shape.sliceArray(size - 2 until size)
@@ -122,11 +122,11 @@ public object DoubleLinearOpsTensorAlgebra :
         return Triple(uTensor.transpose(), sTensor, vTensor.transpose())
     }
 
-    override fun TensorStructure<Double>.symEig(): Pair<DoubleTensor, DoubleTensor> =
+    override fun Tensor<Double>.symEig(): Pair<DoubleTensor, DoubleTensor> =
         symEig(epsilon = 1e-15)
 
     //For information: http://hua-zhou.github.io/teaching/biostatm280-2017spring/slides/16-eigsvd/eigsvd.html
-    public fun TensorStructure<Double>.symEig(epsilon: Double): Pair<DoubleTensor, DoubleTensor> {
+    public fun Tensor<Double>.symEig(epsilon: Double): Pair<DoubleTensor, DoubleTensor> {
         checkSymmetric(tensor, epsilon)
         val (u, s, v) = tensor.svd(epsilon)
         val shp = s.shape + intArrayOf(1)
@@ -139,7 +139,7 @@ public object DoubleLinearOpsTensorAlgebra :
         return eig to v
     }
 
-    public fun TensorStructure<Double>.detLU(epsilon: Double = 1e-9): DoubleTensor {
+    public fun Tensor<Double>.detLU(epsilon: Double = 1e-9): DoubleTensor {
 
         checkSquareMatrix(tensor.shape)
         val luTensor = tensor.copy()
@@ -164,7 +164,7 @@ public object DoubleLinearOpsTensorAlgebra :
         return detTensor
     }
 
-    public fun TensorStructure<Double>.invLU(epsilon: Double = 1e-9): DoubleTensor {
+    public fun Tensor<Double>.invLU(epsilon: Double = 1e-9): DoubleTensor {
         val (luTensor, pivotsTensor) = luFactor(epsilon)
         val invTensor = luTensor.zeroesLike()
 
@@ -177,11 +177,11 @@ public object DoubleLinearOpsTensorAlgebra :
         return invTensor
     }
 
-    public fun TensorStructure<Double>.lu(epsilon: Double = 1e-9): Triple<DoubleTensor, DoubleTensor, DoubleTensor> {
+    public fun Tensor<Double>.lu(epsilon: Double = 1e-9): Triple<DoubleTensor, DoubleTensor, DoubleTensor> {
         val (lu, pivots) = this.luFactor(epsilon)
         return luPivot(lu, pivots)
     }
 
-    override fun TensorStructure<Double>.lu(): Triple<DoubleTensor, DoubleTensor, DoubleTensor> = lu(1e-9)
+    override fun Tensor<Double>.lu(): Triple<DoubleTensor, DoubleTensor, DoubleTensor> = lu(1e-9)
 
 }
\ No newline at end of file
diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/DoubleTensorAlgebra.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/DoubleTensorAlgebra.kt
index d3e8bf175..4009f7b45 100644
--- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/DoubleTensorAlgebra.kt
+++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/DoubleTensorAlgebra.kt
@@ -7,7 +7,7 @@ package space.kscience.kmath.tensors.core.algebras
 
 import space.kscience.kmath.nd.as2D
 import space.kscience.kmath.tensors.api.TensorPartialDivisionAlgebra
-import space.kscience.kmath.tensors.api.TensorStructure
+import space.kscience.kmath.tensors.api.Tensor
 import space.kscience.kmath.tensors.core.*
 import space.kscience.kmath.tensors.core.broadcastOuterTensors
 import space.kscience.kmath.tensors.core.checkBufferShapeConsistency
@@ -25,7 +25,7 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
 
     public companion object : DoubleTensorAlgebra()
 
-    override fun TensorStructure<Double>.value(): Double {
+    override fun Tensor<Double>.value(): Double {
         check(tensor.shape contentEquals intArrayOf(1)) {
             "Inconsistent value for tensor of shape ${shape.toList()}"
         }
@@ -39,7 +39,7 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
         return DoubleTensor(shape, buffer, 0)
     }
 
-    override operator fun TensorStructure<Double>.get(i: Int): DoubleTensor {
+    override operator fun Tensor<Double>.get(i: Int): DoubleTensor {
         val lastShape = tensor.shape.drop(1).toIntArray()
         val newShape = if (lastShape.isNotEmpty()) lastShape else intArrayOf(1)
         val newStart = newShape.reduce(Int::times) * i + tensor.bufferStart
@@ -52,7 +52,7 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
         return DoubleTensor(shape, buffer)
     }
 
-    public fun TensorStructure<Double>.fullLike(value: Double): DoubleTensor {
+    public fun Tensor<Double>.fullLike(value: Double): DoubleTensor {
         val shape = tensor.shape
         val buffer = DoubleArray(tensor.numElements) { value }
         return DoubleTensor(shape, buffer)
@@ -60,11 +60,11 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
 
     public fun zeros(shape: IntArray): DoubleTensor = full(0.0, shape)
 
-    public fun TensorStructure<Double>.zeroesLike(): DoubleTensor = tensor.fullLike(0.0)
+    public fun Tensor<Double>.zeroesLike(): DoubleTensor = tensor.fullLike(0.0)
 
     public fun ones(shape: IntArray): DoubleTensor = full(1.0, shape)
 
-    public fun TensorStructure<Double>.onesLike(): DoubleTensor = tensor.fullLike(1.0)
+    public fun Tensor<Double>.onesLike(): DoubleTensor = tensor.fullLike(1.0)
 
     public fun eye(n: Int): DoubleTensor {
         val shape = intArrayOf(n, n)
@@ -76,20 +76,20 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
         return res
     }
 
-    public fun TensorStructure<Double>.copy(): DoubleTensor {
+    public fun Tensor<Double>.copy(): DoubleTensor {
         return DoubleTensor(tensor.shape, tensor.mutableBuffer.array().copyOf(), tensor.bufferStart)
     }
 
-    override fun Double.plus(other: TensorStructure<Double>): DoubleTensor {
+    override fun Double.plus(other: Tensor<Double>): DoubleTensor {
         val resBuffer = DoubleArray(other.tensor.numElements) { i ->
             other.tensor.mutableBuffer.array()[other.tensor.bufferStart + i] + this
         }
         return DoubleTensor(other.shape, resBuffer)
     }
 
-    override fun TensorStructure<Double>.plus(value: Double): DoubleTensor = value + tensor
+    override fun Tensor<Double>.plus(value: Double): DoubleTensor = value + tensor
 
-    override fun TensorStructure<Double>.plus(other: TensorStructure<Double>): DoubleTensor {
+    override fun Tensor<Double>.plus(other: Tensor<Double>): DoubleTensor {
         checkShapesCompatible(tensor, other.tensor)
         val resBuffer = DoubleArray(tensor.numElements) { i ->
             tensor.mutableBuffer.array()[i] + other.tensor.mutableBuffer.array()[i]
@@ -97,13 +97,13 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
         return DoubleTensor(tensor.shape, resBuffer)
     }
 
-    override fun TensorStructure<Double>.plusAssign(value: Double) {
+    override fun Tensor<Double>.plusAssign(value: Double) {
         for (i in 0 until tensor.numElements) {
             tensor.mutableBuffer.array()[tensor.bufferStart + i] += value
         }
     }
 
-    override fun TensorStructure<Double>.plusAssign(other: TensorStructure<Double>) {
+    override fun Tensor<Double>.plusAssign(other: Tensor<Double>) {
         checkShapesCompatible(tensor, other.tensor)
         for (i in 0 until tensor.numElements) {
             tensor.mutableBuffer.array()[tensor.bufferStart + i] +=
@@ -111,21 +111,21 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
         }
     }
 
-    override fun Double.minus(other: TensorStructure<Double>): DoubleTensor {
+    override fun Double.minus(other: Tensor<Double>): DoubleTensor {
         val resBuffer = DoubleArray(other.tensor.numElements) { i ->
             this - other.tensor.mutableBuffer.array()[other.tensor.bufferStart + i]
         }
         return DoubleTensor(other.shape, resBuffer)
     }
 
-    override fun TensorStructure<Double>.minus(value: Double): DoubleTensor {
+    override fun Tensor<Double>.minus(value: Double): DoubleTensor {
         val resBuffer = DoubleArray(tensor.numElements) { i ->
             tensor.mutableBuffer.array()[tensor.bufferStart + i] - value
         }
         return DoubleTensor(tensor.shape, resBuffer)
     }
 
-    override fun TensorStructure<Double>.minus(other: TensorStructure<Double>): DoubleTensor {
+    override fun Tensor<Double>.minus(other: Tensor<Double>): DoubleTensor {
         checkShapesCompatible(tensor, other)
         val resBuffer = DoubleArray(tensor.numElements) { i ->
             tensor.mutableBuffer.array()[i] - other.tensor.mutableBuffer.array()[i]
@@ -133,13 +133,13 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
         return DoubleTensor(tensor.shape, resBuffer)
     }
 
-    override fun TensorStructure<Double>.minusAssign(value: Double) {
+    override fun Tensor<Double>.minusAssign(value: Double) {
         for (i in 0 until tensor.numElements) {
             tensor.mutableBuffer.array()[tensor.bufferStart + i] -= value
         }
     }
 
-    override fun TensorStructure<Double>.minusAssign(other: TensorStructure<Double>) {
+    override fun Tensor<Double>.minusAssign(other: Tensor<Double>) {
         checkShapesCompatible(tensor, other)
         for (i in 0 until tensor.numElements) {
             tensor.mutableBuffer.array()[tensor.bufferStart + i] -=
@@ -147,16 +147,16 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
         }
     }
 
-    override fun Double.times(other: TensorStructure<Double>): DoubleTensor {
+    override fun Double.times(other: Tensor<Double>): DoubleTensor {
         val resBuffer = DoubleArray(other.tensor.numElements) { i ->
             other.tensor.mutableBuffer.array()[other.tensor.bufferStart + i] * this
         }
         return DoubleTensor(other.shape, resBuffer)
     }
 
-    override fun TensorStructure<Double>.times(value: Double): DoubleTensor = value * tensor
+    override fun Tensor<Double>.times(value: Double): DoubleTensor = value * tensor
 
-    override fun TensorStructure<Double>.times(other: TensorStructure<Double>): DoubleTensor {
+    override fun Tensor<Double>.times(other: Tensor<Double>): DoubleTensor {
         checkShapesCompatible(tensor, other)
         val resBuffer = DoubleArray(tensor.numElements) { i ->
             tensor.mutableBuffer.array()[tensor.bufferStart + i] *
@@ -165,13 +165,13 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
         return DoubleTensor(tensor.shape, resBuffer)
     }
 
-    override fun TensorStructure<Double>.timesAssign(value: Double) {
+    override fun Tensor<Double>.timesAssign(value: Double) {
         for (i in 0 until tensor.numElements) {
             tensor.mutableBuffer.array()[tensor.bufferStart + i] *= value
         }
     }
 
-    override fun TensorStructure<Double>.timesAssign(other: TensorStructure<Double>) {
+    override fun Tensor<Double>.timesAssign(other: Tensor<Double>) {
         checkShapesCompatible(tensor, other)
         for (i in 0 until tensor.numElements) {
             tensor.mutableBuffer.array()[tensor.bufferStart + i] *=
@@ -179,21 +179,21 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
         }
     }
 
-    override fun Double.div(other: TensorStructure<Double>): DoubleTensor {
+    override fun Double.div(other: Tensor<Double>): DoubleTensor {
         val resBuffer = DoubleArray(other.tensor.numElements) { i ->
             this / other.tensor.mutableBuffer.array()[other.tensor.bufferStart + i]
         }
         return DoubleTensor(other.shape, resBuffer)
     }
 
-    override fun TensorStructure<Double>.div(value: Double): DoubleTensor {
+    override fun Tensor<Double>.div(value: Double): DoubleTensor {
         val resBuffer = DoubleArray(tensor.numElements) { i ->
             tensor.mutableBuffer.array()[tensor.bufferStart + i] / value
         }
         return DoubleTensor(shape, resBuffer)
     }
 
-    override fun TensorStructure<Double>.div(other: TensorStructure<Double>): DoubleTensor {
+    override fun Tensor<Double>.div(other: Tensor<Double>): DoubleTensor {
         checkShapesCompatible(tensor, other)
         val resBuffer = DoubleArray(tensor.numElements) { i ->
             tensor.mutableBuffer.array()[other.tensor.bufferStart + i] /
@@ -202,13 +202,13 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
         return DoubleTensor(tensor.shape, resBuffer)
     }
 
-    override fun TensorStructure<Double>.divAssign(value: Double) {
+    override fun Tensor<Double>.divAssign(value: Double) {
         for (i in 0 until tensor.numElements) {
             tensor.mutableBuffer.array()[tensor.bufferStart + i] /= value
         }
     }
 
-    override fun TensorStructure<Double>.divAssign(other: TensorStructure<Double>) {
+    override fun Tensor<Double>.divAssign(other: Tensor<Double>) {
         checkShapesCompatible(tensor, other)
         for (i in 0 until tensor.numElements) {
             tensor.mutableBuffer.array()[tensor.bufferStart + i] /=
@@ -216,14 +216,14 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
         }
     }
 
-    override fun TensorStructure<Double>.unaryMinus(): DoubleTensor {
+    override fun Tensor<Double>.unaryMinus(): DoubleTensor {
         val resBuffer = DoubleArray(tensor.numElements) { i ->
             tensor.mutableBuffer.array()[tensor.bufferStart + i].unaryMinus()
         }
         return DoubleTensor(tensor.shape, resBuffer)
     }
 
-    override fun TensorStructure<Double>.transpose(i: Int, j: Int): DoubleTensor {
+    override fun Tensor<Double>.transpose(i: Int, j: Int): DoubleTensor {
         val ii = tensor.minusIndex(i)
         val jj = tensor.minusIndex(j)
         checkTranspose(tensor.dimension, ii, jj)
@@ -248,16 +248,16 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
     }
 
 
-    override fun TensorStructure<Double>.view(shape: IntArray): DoubleTensor {
+    override fun Tensor<Double>.view(shape: IntArray): DoubleTensor {
         checkView(tensor, shape)
         return DoubleTensor(shape, tensor.mutableBuffer.array(), tensor.bufferStart)
     }
 
-    override fun TensorStructure<Double>.viewAs(other: TensorStructure<Double>): DoubleTensor {
+    override fun Tensor<Double>.viewAs(other: Tensor<Double>): DoubleTensor {
         return tensor.view(other.shape)
     }
 
-    override infix fun TensorStructure<Double>.dot(other: TensorStructure<Double>): DoubleTensor {
+    override infix fun Tensor<Double>.dot(other: Tensor<Double>): DoubleTensor {
         if (tensor.shape.size == 1 && other.shape.size == 1) {
             return DoubleTensor(intArrayOf(1), doubleArrayOf(tensor.times(other).tensor.mutableBuffer.array().sum()))
         }
@@ -309,7 +309,7 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
         return resTensor
     }
 
-    override fun diagonalEmbedding(diagonalEntries: TensorStructure<Double>, offset: Int, dim1: Int, dim2: Int):
+    override fun diagonalEmbedding(diagonalEntries: Tensor<Double>, offset: Int, dim1: Int, dim2: Int):
             DoubleTensor {
         val n = diagonalEntries.shape.size
         val d1 = minusIndexFrom(n + 1, dim1)
@@ -358,7 +358,7 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
     }
 
 
-    public fun TensorStructure<Double>.map(transform: (Double) -> Double): DoubleTensor {
+    public fun Tensor<Double>.map(transform: (Double) -> Double): DoubleTensor {
         return DoubleTensor(
             tensor.shape,
             tensor.mutableBuffer.array().map { transform(it) }.toDoubleArray(),
@@ -366,14 +366,14 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
         )
     }
 
-    public fun TensorStructure<Double>.eq(other: TensorStructure<Double>, epsilon: Double): Boolean {
+    public fun Tensor<Double>.eq(other: Tensor<Double>, epsilon: Double): Boolean {
         return tensor.eq(other) { x, y -> abs(x - y) < epsilon }
     }
 
-    public infix fun TensorStructure<Double>.eq(other: TensorStructure<Double>): Boolean = tensor.eq(other, 1e-5)
+    public infix fun Tensor<Double>.eq(other: Tensor<Double>): Boolean = tensor.eq(other, 1e-5)
 
-    private fun TensorStructure<Double>.eq(
-        other: TensorStructure<Double>,
+    private fun Tensor<Double>.eq(
+        other: Tensor<Double>,
         eqFunction: (Double, Double) -> Boolean
     ): Boolean {
         checkShapesCompatible(tensor, other)
@@ -396,7 +396,7 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
     public fun randomNormal(shape: IntArray, seed: Long = 0): DoubleTensor =
         DoubleTensor(shape, getRandomNormals(shape.reduce(Int::times), seed))
 
-    public fun TensorStructure<Double>.randomNormalLike(seed: Long = 0): DoubleTensor =
+    public fun Tensor<Double>.randomNormalLike(seed: Long = 0): DoubleTensor =
         DoubleTensor(tensor.shape, getRandomNormals(tensor.shape.reduce(Int::times), seed))
 
     // stack tensors by axis 0
@@ -412,7 +412,7 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
     }
 
     // build tensor from this rows by given indices
-    public fun TensorStructure<Double>.rowsByIndices(indices: IntArray): DoubleTensor {
+    public fun Tensor<Double>.rowsByIndices(indices: IntArray): DoubleTensor {
         return stack(indices.map { this[it] })
     }
 }
diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/checks.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/checks.kt
index b1c12ccde..f8bd5027a 100644
--- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/checks.kt
+++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/checks.kt
@@ -1,6 +1,6 @@
 package space.kscience.kmath.tensors.core
 
-import space.kscience.kmath.tensors.api.TensorStructure
+import space.kscience.kmath.tensors.api.Tensor
 import space.kscience.kmath.tensors.core.algebras.DoubleLinearOpsTensorAlgebra
 import space.kscience.kmath.tensors.core.algebras.DoubleTensorAlgebra
 
@@ -20,7 +20,7 @@ internal fun checkBufferShapeConsistency(shape: IntArray, buffer: DoubleArray) =
         "Inconsistent shape ${shape.toList()} for buffer of size ${buffer.size} provided"
     }
 
-internal fun <T> checkShapesCompatible(a: TensorStructure<T>, b: TensorStructure<T>) =
+internal fun <T> checkShapesCompatible(a: Tensor<T>, b: Tensor<T>) =
     check(a.shape contentEquals b.shape) {
         "Incompatible shapes ${a.shape.toList()} and ${b.shape.toList()} "
     }
@@ -30,7 +30,7 @@ internal fun checkTranspose(dim: Int, i: Int, j: Int) =
         "Cannot transpose $i to $j for a tensor of dim $dim"
     }
 
-internal fun <T> checkView(a: TensorStructure<T>, shape: IntArray) =
+internal fun <T> checkView(a: Tensor<T>, shape: IntArray) =
     check(a.shape.reduce(Int::times) == shape.reduce(Int::times))
 
 internal fun checkSquareMatrix(shape: IntArray) {
@@ -44,7 +44,7 @@ internal fun checkSquareMatrix(shape: IntArray) {
 }
 
 internal fun DoubleTensorAlgebra.checkSymmetric(
-    tensor: TensorStructure<Double>, epsilon: Double = 1e-6
+    tensor: Tensor<Double>, epsilon: Double = 1e-6
 ) =
     check(tensor.eq(tensor.transpose(), epsilon)) {
         "Tensor is not symmetric about the last 2 dimensions at precision $epsilon"