Example implementation of the L0 regularization method described at
Learning Sparse Neural Networks through L0 regularization, Christos Louizos, Max Welling & Diederik P. Kingma, https://openreview.net/pdf?id=BkdI3hgRZ
This code is provided as is and is not maintained / updated.
Use Jax functions in Pytorch with DLPack
TODO: update this README! Fast Discounted Cumulative Sums in PyTorch This repository implements an efficient parallel algorithm for the computation of
motor-system Introduction A code copied from google-research which named motion-imitation was rewrited with PyTorch. More details can get from this pr
Bunch of optimizer implementations in PyTorch
AccSGD This is the code associated with Accelerated SGD algorithm used in the paper On the insufficiency of existing momentum schemes for Stochastic O
(Generic) EfficientNets for PyTorch A 'generic' implementation of EfficientNet, MixNet, MobileNetV3, etc. that covers most of the compute/parameter ef
glow-pytorch PyTorch implementation of Glow, Generative Flow with Invertible 1x1 Convolutions
Pytorch bindings for Fortran
Opacus is a library that enables training PyTorch models with differential privacy. It supports training with minimal code changes required on the cli
A PyTorch repo for data loading and utilities to be shared by the PyTorch domain libraries.
RAdam On the Variance of the Adaptive Learning Rate and Beyond We are in an early-release beta. Expect some adventures and rough edges. Table of Conte
For something in between a pytorch and a karpathy/micrograd This may not be the best deep learning framework, but it is a deep learning framework. Due
geoopt Manifold aware pytorch.optim. Unofficial implementation for “Riemannian Adaptive Optimization Methods” ICLR2019 and more. Installation Make sur
PyTorch wrappers for using your model in audacity!
Code release for "Bayesian Compression for Deep Learning" In "Bayesian Compression for Deep Learning" we adopt a Bayesian view for the compression of
Performer - Pytorch An implementation of Performer, a linear attention-based transformer variant with a Fast Attention Via positive Orthogonal Random
PyTorch framework A simple and complete framework for PyTorch, providing a variety of data loading and simple task solutions that are easy to extend and migrate
Reformer, the Efficient Transformer, in Pytorch This is a Pytorch implementation of Reformer https://openreview.net/pdf?id=rkgNKkHtvB It includes LSH
PyTorch Implementation of Differentiable ODE Solvers This library provides ordinary differential equation (ODE) solvers implemented in PyTorch. Backpr
Unofficial PyTorch implementation of DeepMind's Perceiver IO with PyTorch Lightning scripts for distributed training
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