Acorns
https://arxiv.org/pdf/2007.05094.pdf An Easy-To-Use Code Generator for Gradients and Hessians
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Functorch | 1,369 |  | 12 | 11 days ago | 7 | July 05, 2022 | 247 | bsd-3-clause | Jupyter Notebook | |
| functorch is JAX-like composable function transforms for PyTorch. | ||||||||||
| Finitediff.jl | 221 | 3 months ago | 17 | other | Julia | |||||
| Fast non-allocating calculations of gradients, Jacobians, and Hessians with sparsity support | ||||||||||
| Numdifftools | 182 |  | 12 | 102 | a year ago | 25 | November 10, 2022 | 10 | bsd-3-clause | Python |
| Solve automatic numerical differentiation problems in one or more variables. | ||||||||||
| Path_explain | 134 | 2 years ago | 7 | September 13, 2021 | 3 | mit | Jupyter Notebook | |||
| A repository for explaining feature attributions and feature interactions in deep neural networks. | ||||||||||
| Psgd_torch | 86 | 3 months ago | Python | |||||||
| Pytorch implementation of preconditioned stochastic gradient descent (affine group preconditioner, low-rank approximation preconditioner and more) | ||||||||||
| Calculus | 41 | 2 | a year ago | 11 | March 09, 2023 | gpl-3.0 | R | |||
| High Dimensional Numerical and Symbolic Calculus in R | ||||||||||
| Psgd_tf | 34 | 5 months ago | Python | |||||||
| Tensorflow implementation of preconditioned stochastic gradient descent | ||||||||||
| Optinpy | 28 | 3 years ago | gpl-3.0 | Python | ||||||
| Optimization in Python: Linear and non-linear optimization methods. | ||||||||||
| Nlsolvers.jl | 26 | 3 months ago | 19 | mit | Julia | |||||
| No bells and whistles foundation of Optim.jl | ||||||||||
| Acorns | 21 | 3 years ago | 7 | January 18, 2021 | 1 | mit | Python | |||
| https://arxiv.org/pdf/2007.05094.pdf An Easy-To-Use Code Generator for Gradients and Hessians | ||||||||||
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