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-DPPO Pytorch implementation of Distributed Proximal Policy Optimization: https://arxiv.org/abs/1707.02286 Using PPO with clip loss (from https
Example implementation of the L0 regularization method described at Learning Sparse Neural Networks through L0 regularization, Christos Louizos, Max W
Pretrained models for Pytorch (Work in progress) The goal of this repo is: to help to reproduce research papers results (transfer learning setups for
News March 3: v0.9.97 has various bug fixes and improvements: Bug fixes for NTXentLoss Efficiency improvement for AccuracyCalculator, by using torch i
Opacus is a library that enables training PyTorch models with differential privacy. It supports training with minimal code changes required on the cli
AccSGD This is the code associated with Accelerated SGD algorithm used in the paper On the insufficiency of existing momentum schemes for Stochastic O
higher is a library providing support for higher-order optimization, e.g. through unrolled first-order optimization loops, of "meta" aspects of these
PyTorch wrappers for using your model in audacity!
Tensor Sensor See article Clarifying exceptions and visualizing tensor operations in deep learning code. One of the biggest challenges when writing co
PyTorch misc Collection of code snippets I've written for the PyTorch discussion board. All scripts were testes using the PyTorch 1.0 preview and torc
PyTorch implementations of normalizing flow and its variants.
CompactBilinearPooling-Pytorch A Pytorch Implementation for Compact Bilinear Pooling. Adapted from tensorflow_compact_bilinear_pooling Prerequisites I
PyTorch Sparse This package consists of a small extension library of optimized sparse matrix operations with autograd support. This package currently
Antialiased CNNs [Project Page] [Paper] [Talk] Making Convolutional Networks Shift-Invariant Again Richard Zhang. In ICML, 2019. Quick & easy start Ru
micrograd A tiny Autograd engine (with a bite! :)). Implements backpropagation (reverse-mode autodiff) over a dynamically built DAG and a small neural
GPU-accelerated PyTorch implementation of Zero-shot User Intent Detection via Capsule Neural Networks This repository implements a capsule model Inten
EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis This repo contains the official implementations of EigenDamage: Structured Prunin
AdaBound An optimizer that trains as fast as Adam and as good as SGD, for developing state-of-the-art deep learning models on a wide variety of popula
Wiki and tutorials | Documentation | Getting Started | Algorithms | Design | FAQ Distiller is an open-source Python package for neural network compres
PyTorch-LBFGS: A PyTorch Implementation of L-BFGS Authors: Hao-Jun Michael Shi (Northwestern University) and Dheevatsa Mudigere (Facebook) What is it?
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