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Deep learning in Rust, with shape checked tensors and neural networks
Created
2021-10-12
890 commits to main branch, last one 8 months ago
automatic differentiation made easier for C++
Created
2018-07-19
589 commits to main branch, last one 3 months ago
Tensors and dynamic neural networks in pure Rust.
Created
2021-02-13
119 commits to main branch, last one about a year ago
Transparent calculations with uncertainties on the quantities involved (aka "error propagation"); calculation of derivatives.
Created
2010-06-11
2,648 commits to master branch, last one 8 days ago
Drop-in autodiff for NumPy.
Created
2017-07-17
1,584 commits to master branch, last one 16 days 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
Differentiate python calls from Julia
Created
2022-01-20
75 commits to main branch, last one 2 years ago
Fazang is a Fortran library for reverse-mode automatic differentiation, inspired by Stan/Math library.
Created
2022-01-24
66 commits to main branch, last one 2 years ago