Minkowski Engine is an auto-diff neural network library for high-dimensional sparse tensors
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Updated
Mar 5, 2024 - Python
Minkowski Engine is an auto-diff neural network library for high-dimensional sparse tensors
automatic differentiation made easier for C
Computational graphs with reverse automatic differentation in the GPU
Iterative Linear Quadratic Regulator with auto-differentiatiable dynamics models
skscope: Sparse-Constrained OPtimization via itErative-solvers
Enzyme integration into Rust. Experimental, do not use.
FastAD is a C implementation of automatic differentiation both forward and reverse mode.
AutoDiff DAG constructor, built on numpy and Cython. A Neural Turing Machine and DeepQ agent run on it. Clean code for educational purpose.
Сustom torch style machine learning framework with automatic differentiation implemented on numpy, allows build GANs, VAEs, etc.
Differentiable Reacting Flow Modeling Software
도서 머신러닝·딥러닝에 필요한 기초 수학 with 파이썬의 예제 코드와 그래프 그리는 코드 및 웹앱 저장소
variational quantum circuit simulator in Julia, under GPLv3
Galactic and Gravitational Dynamics in Python ( GPU and autodiff)
Differentiable Gaussian Process implementation for PyTorch
Algorithmic differentiation with hyper-dual numbers in C and Python
Auto-differentiation library for C
Fortran backward (reverse) mode automatic differentiation.
JutulDarcyRules: ChainRules extension to Jutul and JutulDarcy
Tiny calculation graph library
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