35 results found Sort:

458
9.2k
apache-2.0
66
Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals.
Created 2022-07-18
1,583 commits to main branch, last one 19 hours ago
435
2.3k
apache-2.0
66
Source-to-Source Debuggable Derivatives in Pure Python
This repository has been archived (exclude archived)
Created 2017-10-26
68 commits to master branch, last one 6 years ago
99
1.8k
other
35
Deep learning in Rust, with shape checked tensors and neural networks
Created 2021-10-12
890 commits to main branch, last one 11 months ago
173
1.7k
mit
43
automatic differentiation made easier for C++
Created 2018-07-19
596 commits to main branch, last one about a month ago
68
591
bsd-2-clause
40
DiffSharp: Differentiable Functional Programming
Created 2014-08-28
2,131 commits to dev branch, last one about a year ago
77
590
other
13
Transparent calculations with uncertainties on the quantities involved (aka "error propagation"); calculation of derivatives.
Created 2010-06-11
2,650 commits to master branch, last one about a month ago
This repository has no description...
Created 2022-01-03
55 commits to main branch, last one about a year ago
25
399
mit
10
End-to-end Generative Optimization for AI Agents
Created 2024-06-14
364 commits to main branch, last one 10 days ago
19
355
apache-2.0
10
AutoBound automatically computes upper and lower bounds on functions.
Created 2022-11-23
40 commits to main branch, last one about a year ago
27
334
apache-2.0
8
Betty: an automatic differentiation library for generalized meta-learning and multilevel optimization
Created 2022-06-29
453 commits to main branch, last one 5 months ago
An interface to various automatic differentiation backends in Julia.
Created 2024-01-09
412 commits to main branch, last one 14 days ago
21
197
mit
16
Drop-in autodiff for NumPy.
Created 2017-07-17
1,584 commits to master branch, last one 3 months ago
37
146
apache-2.0
14
A JIT compiler for hybrid quantum programs in PennyLane
Created 2023-02-17
951 commits to main branch, last one 12 hours ago
[Experimental] Graph and Tensor Abstraction for Deep Learning all in Common Lisp
This repository has been archived (exclude archived)
Created 2023-05-21
1,436 commits to master branch, last one 10 days ago
7
125
apache-2.0
4
Tensors and dynamic Neural Networks in Mojo
Created 2023-09-23
79 commits to main branch, last one 5 months ago
Automatic differentiation of implicit functions
Created 2022-03-28
146 commits to main branch, last one 2 months ago
14
120
apache-2.0
4
Minimal deep learning library written from scratch in Python, using NumPy/CuPy.
Created 2021-02-03
136 commits to main branch, last one 2 years ago
0
119
apache-2.0
7
An experimental deep learning framework for Nim based on a differentiable array programming language
Created 2021-10-06
143 commits to main branch, last one about a year ago
14
113
apache-2.0
15
A probabilistic programming language that combines automatic differentiation, automatic marginalization, and automatic conditioning within Monte Carlo methods.
Created 2016-12-29
5,236 commits to master branch, last one 2 days ago
10
112
mit
21
Solve ODEs fast, with support for PyMC
Created 2019-08-08
162 commits to master branch, last one 7 months ago
FastAD is a C++ implementation of automatic differentiation both forward and reverse mode.
Created 2019-04-17
375 commits to master branch, last one about a year ago
A .NET library that provides fast, accurate and automatic differentiation (computes derivative / gradient) of mathematical functions.
Created 2017-08-03
142 commits to master branch, last one 6 years ago
Geometry processing utilities compatible with jax for autodifferentiation.
Created 2021-08-05
36 commits to main branch, last one 2 years ago
基于Python的numpy实现的简易深度学习框架,包括自动求导、优化器、layer等的实现。
Created 2021-04-02
11 commits to main branch, last one 3 years ago
5
68
other
15
A operator overloading, tape-based, reverse-mode AD
This repository has been archived (exclude archived)
Created 2017-03-23
335 commits to master branch, last one about a year ago
Сustom torch style machine learning framework with automatic differentiation implemented on numpy, allows build GANs, VAEs, etc.
Created 2022-02-21
116 commits to master branch, last one 4 months ago
7
54
bsd-3-clause
5
Differentiable optical models as parameterised neural networks in Jax using Zodiax
Created 2022-04-29
834 commits to main branch, last one 2 months ago
11
53
bsd-3-clause
13
library of C++ functions that support applications of Stan in Pharmacometrics
Created 2018-03-09
601 commits to master branch, last one about a month ago
Utilities for testing custom AD primitives.
Created 2020-01-22
453 commits to main branch, last one 4 months ago
JAX-DIPS is a differentiable interfacial PDE solver.
Created 2021-10-19
579 commits to main branch, last one 3 months ago