diff --git a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jTensorAlgebra.kt b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jTensorAlgebra.kt
index bc58eefc3..6e84371ae 100644
--- a/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jTensorAlgebra.kt
+++ b/kmath-nd4j/src/main/kotlin/space/kscience/kmath/nd4j/Nd4jTensorAlgebra.kt
@@ -28,8 +28,6 @@ public sealed interface Nd4jTensorAlgebra<T : Number> : AnalyticTensorAlgebra<T>
      */
     public fun INDArray.wrap(): Nd4jArrayStructure<T>
 
-    public fun INDArray.wrapInt(): Nd4jArrayStructure<Int>
-
     /**
      * Unwraps to or acquires [INDArray] from [StructureND].
      */
@@ -93,7 +91,7 @@ public sealed interface Nd4jTensorAlgebra<T : Number> : AnalyticTensorAlgebra<T>
     public override fun Tensor<T>.viewAs(other: Tensor<T>): Tensor<T> = view(other.shape)
 
     override fun Tensor<T>.argMax(dim: Int, keepDim: Boolean): Tensor<Int> =
-        ndBase.get().argmax(ndArray, keepDim, dim).wrapInt()
+        ndBase.get().argmax(ndArray, keepDim, dim).asIntStructure()
 
     public override fun Tensor<T>.mean(dim: Int, keepDim: Boolean): Tensor<T> = ndArray.mean(keepDim, dim).wrap()
 
@@ -146,7 +144,6 @@ public sealed interface Nd4jTensorAlgebra<T : Number> : AnalyticTensorAlgebra<T>
  */
 public object DoubleNd4jTensorAlgebra : Nd4jTensorAlgebra<Double> {
     public override fun INDArray.wrap(): Nd4jArrayStructure<Double> = asDoubleStructure()
-    public override fun INDArray.wrapInt(): Nd4jArrayStructure<Int> = asIntStructure()
 
     @OptIn(PerformancePitfall::class)
     public override val StructureND<Double>.ndArray: INDArray
diff --git a/kmath-noa/src/main/java/space/kscience/kmath/noa/JNoa.java b/kmath-noa/src/main/java/space/kscience/kmath/noa/JNoa.java
index 20f8c7510..f2d65aa5c 100644
--- a/kmath-noa/src/main/java/space/kscience/kmath/noa/JNoa.java
+++ b/kmath-noa/src/main/java/space/kscience/kmath/noa/JNoa.java
@@ -191,6 +191,18 @@ class JNoa {
 
     public static native long sumDimTensor(long tensorHandle, int dim, boolean keepDim);
 
+    public static native long minTensor(long tensorHandle);
+
+    public static native long minDimTensor(long tensorHandle, int dim, boolean keepDim);
+
+    public static native long maxTensor(long tensorHandle);
+
+    public static native long maxDimTensor(long tensorHandle, int dim, boolean keepDim);
+
+    public static native long argMaxTensor(long tensorHandle, int dim, boolean keepDim);
+
+    public static native long flattenTensor(long tensorHandle);
+
     public static native long matmul(long lhs, long rhs);
 
     public static native void matmulAssign(long lhs, long rhs);
diff --git a/kmath-noa/src/main/kotlin/space/kscience/kmath/noa/algebras.kt b/kmath-noa/src/main/kotlin/space/kscience/kmath/noa/algebras.kt
index a5d69b6bd..3a0ce28df 100644
--- a/kmath-noa/src/main/kotlin/space/kscience/kmath/noa/algebras.kt
+++ b/kmath-noa/src/main/kotlin/space/kscience/kmath/noa/algebras.kt
@@ -100,6 +100,22 @@ constructor(protected val scope: NoaScope) : TensorAlgebra<T> {
     override fun Tensor<T>.sum(dim: Int, keepDim: Boolean): TensorType =
         wrap(JNoa.sumDimTensor(this.cast().tensorHandle, dim, keepDim))
 
+    public fun Tensor<T>.minAll(): TensorType = wrap(JNoa.minTensor(this.cast().tensorHandle))
+    override fun Tensor<T>.min(): T = minAll().item()
+    override fun Tensor<T>.min(dim: Int, keepDim: Boolean): TensorType =
+        wrap(JNoa.minDimTensor(this.cast().tensorHandle, dim, keepDim))
+
+    public fun Tensor<T>.maxAll(): TensorType = wrap(JNoa.maxTensor(this.cast().tensorHandle))
+    override fun Tensor<T>.max(): T = maxAll().item()
+    override fun Tensor<T>.max(dim: Int, keepDim: Boolean): TensorType =
+        wrap(JNoa.maxDimTensor(this.cast().tensorHandle, dim, keepDim))
+
+    override fun Tensor<T>.argMax(dim: Int, keepDim: Boolean): NoaIntTensor =
+        NoaIntTensor(scope, JNoa.argMaxTensor(this.cast().tensorHandle, dim, keepDim))
+
+    public fun Tensor<T>.flatten(): TensorType =
+        wrap(JNoa.flattenTensor(this.cast().tensorHandle))
+
     public fun Tensor<T>.copy(): TensorType =
         wrap(JNoa.copyTensor(this.cast().tensorHandle))