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.
PyTorch Implementation of Differentiable SDE Solvers This library provides stochastic differential equation (SDE) solvers with GPU support and efficie
A lightweight wrapper for PyTorch that provides a simple declarative API for context switching between devices, distributed modes, mixed-precision, and PyTorch extensions.
Wiki and tutorials | Documentation | Getting Started | Algorithms | Design | FAQ Distiller is an open-source Python package for neural network compres
motor-system Introduction A code copied from google-research which named motion-imitation was rewrited with PyTorch. More details can get from this pr
Intro PyTorch implementation of Learning to learn by gradient descent by gradient descent. Run python main.py TODO Initial implementation Toy data LST
It is a repo that contains scripts that makes using PyTorch on Windows easier. Easy Installation Update: Starting from 0.4.0, you can go to the offici
glow-pytorch PyTorch implementation of Glow, Generative Flow with Invertible 1x1 Convolutions
🤗 Accelerate was created for PyTorch users who like to write the training loop of PyTorch models but are reluctant to write and maintain the boilerplate code needed to use multi-GPUs/TPU/fp16.
PyTorch implementations of normalizing flow and its variants.
PyTorch implementation of [1611.06440 Pruning Convolutional Neural Networks for Resource Efficient Inference] This demonstrates pruning a VGG16 based
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
PyGCL is an open-source library for graph contrastive learning (GCL), which features modularized GCL components from published papers, standardized evaluation, and experiment management.
This is an differentiable pytorch implementation of SIFT patch descriptor. It is very slow for describing one patch, but quite fast for batch. It can
News SRU++, a new SRU variant, is released. [tech report] [blog] The experimental code and SRU++ implementation are available on the dev branch which
PyTorch Scatter Documentation This package consists of a small extension library of highly optimized sparse update (scatter and segment) operations fo
Optimizers and tests Every result is avg of 20 runs. Dataset LR Schedule Imagenette size 128, 5 epoch Imagewoof size 128, 5 epoch Adam - baseline OneC
EfficientNet PyTorch Quickstart Install with pip install efficientnet_pytorch and load a pretrained EfficientNet with: from efficientnet_pytorch impor
GPU-accelerated PyTorch implementation of Zero-shot User Intent Detection via Capsule Neural Networks This repository implements a capsule model Inten
lookahead optimizer for pytorch PyTorch implement of Lookahead Optimizer: k steps forward, 1 step back Usage: base_opt = torch.optim.Adam(model.parame
Unofficial PyTorch implementation of DeepMind's Perceiver IO with PyTorch Lightning scripts for distributed training
1.2k Jan 04, 2023
56 Sep 13, 2022
4.1k Dec 28, 2022
6 Jan 08, 2022
300 Dec 11, 2022
408 Dec 15, 2022
433 Dec 27, 2022
3.5k Jan 08, 2023
55 Dec 01, 2022
836 Dec 26, 2022
12 Dec 19, 2021
592 Jan 07, 2023
150 Dec 24, 2022
2.1k Jan 01, 2023
1.2k Jan 07, 2023
405 Nov 27, 2022
7.2k Jan 06, 2023
15 Dec 24, 2022
318 Dec 09, 2022
251 Dec 25, 2022