78 skills found · Page 1 of 3
arogozhnikov / EinopsFlexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
OpenMined / TenSEALA library for doing homomorphic encryption operations on tensors
analyticalrohit / Pytorch FundamentalsIntroduction to PyTorch, covering tensor initialization, operations, indexing, and reshaping.
johnmarktaylor91 / TorchlensPackage for extracting and mapping the results of every single tensor operation in a PyTorch model in one line of code.
QuantumKitHub / TensorOperations.jlJulia package for tensor contractions and related operations
raskr / Rust AutogradTensors and differentiable operations (like TensorFlow) in Rust
fferflo / EinxUniversal Notation for Tensor Operations in Python
yzhao062 / PytodTOD: GPU-accelerated Outlier Detection via Tensor Operations
MatthewsResearchGroup / TblisTBLIS is a library and framework for performing tensor operations, especially tensor contraction, using efficient native algorithms.
palle-k / DL4SAccelerated tensor operations and dynamic neural networks based on reverse mode automatic differentiation for every device that can run Swift - from watchOS to Linux
ParCIS / MagicubeMagicube is a high-performance library for quantized sparse matrix operations (SpMM and SDDMM) of deep learning on Tensor Cores.
Einsums / EinsumsProvides compile-time contraction pattern analysis to determine optimal tensor operation to perform.
KeitaNakamura / Tensorial.jlStatically sized tensors and related operations for Julia
lsj2408 / Gaunt Tensor Product[ICLR 2024 Spotlight] Official Implementation of "Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt Tensor Products"
cmendl / PytenetPython implementation of quantum tensor network operations and simulations: matrix product states and operators, TDVP time evolution, support for quantum numbers, ...
Quantum-Flytrap / Quantum TensorsQuantum Tensors - NPM package for sparse matrix operations for quantum information and computing
mstksg / Tensor OpsType-safe tensor manipulation operations in Haskell with tensorflow-style automatic differentiation
HyTruongSon / GraphFlowDeep Learning framework in C++/CUDA that supports symbolic/automatic differentiation, dynamic computation graphs, tensor/matrix operations accelerated by GPU and implementations of various state-of-the-art graph neural networks and other Machine Learning models including Covariant Compositional Networks For Learning Graphs [Risi et al]
SciSharp / Tensor.NETA lightweight and high-performance tensor library which provides numpy-like operations but .NET style interfaces. It supports generic tensor, Linq, C# native slices and so on. (Qushui student project))
juanjosegarciaripoll / TensorC++ library for numerical arrays and tensor objects and operations with them, designed to allow Matlab-style programming.
