Tensor (n-dimensional array) library for F#
Core features:
- n-dimensional arrays (tensors) in host memory or on CUDA GPUs
- element-wise operations (addition, multiplication, absolute value, etc.)
- basic linear algebra operations (dot product, SVD decomposition,...
More information
DiffSharp is a tensor library with support for differentiable programming. It is designed for use in machine learning, probabilistic programming, optimization and other domains. For documentation and installation instructions visit: https://diffsharp.github.io/
DiffSharp is a tensor library with support for differentiable programming. It is designed for use in machine learning, probabilistic programming, optimization and other domains. For documentation and installation instructions visit: https://diffsharp.github.io/
DiffSharp is a tensor library with support for differentiable programming. It is designed for use in machine learning, probabilistic programming, optimization and other domains. For documentation and installation instructions visit: https://diffsharp.github.io/
DiffSharp is a tensor library with support for differentiable programming. It is designed for use in machine learning, probabilistic programming, optimization and other domains. For documentation and installation instructions visit: https://diffsharp.github.io/
DiffSharp is a tensor library with support for differentiable programming. It is designed for use in machine learning, probabilistic programming, optimization and other domains. For documentation and installation instructions visit: https://diffsharp.github.io/
DiffSharp is a tensor library with support for differentiable programming. It is designed for use in machine learning, probabilistic programming, optimization and other domains. For documentation and installation instructions visit: https://diffsharp.github.io/
DiffSharp is a tensor library with support for differentiable programming. It is designed for use in machine learning, probabilistic programming, optimization and other domains. For documentation and installation instructions visit: https://diffsharp.github.io/
DiffSharp is a tensor library with support for differentiable programming. It is designed for use in machine learning, probabilistic programming, optimization and other domains. For documentation and installation instructions visit: https://diffsharp.github.io/
Torch7-style tensors and operations on them for C#. All operations are implemented in native code, even the CPU-only [no GPU support] version is extremely fast.
An extended version of the Array to accelerate operation, easy to use, multi dimensional. With SuperchargedArray.Accelerated namespace you will unlock SIMD potential to run the Array operation on any hardware like Intel CPU/GPU, NVIDIA, AMD etc.
Class library implementing advanced mathematical algorithms, transforms, and time series manipulations. Implementations favour simplicity and correctness.
DiffSharp is a tensor library with support for differentiable programming. It is designed for use in machine learning, probabilistic programming, optimization and other domains. For documentation and installation instructions visit: https://diffsharp.github.io/