ATHENA
ATHENA: A Fortran package for neural networks - Published in JOSS (2024)
https://github.com/libxsmm/libxsmm
Library for specialized dense and sparse matrix operations, and deep learning primitives.
fft-conv-pytorch
Implementation of 1D, 2D, and 3D FFT convolutions in PyTorch. Much faster than direct convolutions for large kernel sizes.
tmu
Implements the Tsetlin Machine, Coalesced Tsetlin Machine, Convolutional Tsetlin Machine, Regression Tsetlin Machine, and Weighted Tsetlin Machine, with support for continuous features, drop clause, Type III Feedback, focused negative sampling, multi-task classifier, autoencoder, literal budget, and one-vs-one multi-class classifier. TMU is written in Python with wrappers for C and CUDA-based clause evaluation and updating.
https://github.com/cair/pytsetlinmachine
Implements the Tsetlin Machine, Convolutional Tsetlin Machine, Regression Tsetlin Machine, Weighted Tsetlin Machine, and Embedding Tsetlin Machine, with support for continuous features, multigranularity, clause indexing, and literal budget
https://github.com/cheind/pytorch-debayer
Convolutional PyTorch debayering / demosaicing layers
https://github.com/cair/pytsetlinmachinecuda
Massively Parallel and Asynchronous Architecture for Logic-based AI
https://github.com/cair/pytsetlinmachineparallel
Multi-threaded implementation of the Tsetlin Machine, Convolutional Tsetlin Machine, Regression Tsetlin Machine, and Weighted Tsetlin Machine, with support for continuous features and multigranularity.
https://github.com/cair/convolutional-tsetlin-machine-tutorial
Tutorial on the Convolutional Tsetlin Machine
pytorch-quadconv
Quadrature-based convolutions for deep learning on unstructured and non-uniform mesh data.
time-series-classification
Time Series Classification Analysis of 21 algorithms on the UCR archive datasets + Introduction to a Convolution-based classifier with Feature Selection
