Sparsity-aware deep learning inference runtime for CPUs

Libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models

Code for CRATE (Coding RAte reduction TransformEr).

A research library for pytorch-based neural network pruning, compression, and more.

Complex-valued neural networks for pytorch and Variational Dropout for real and complex layers.

Repository to track the progress in model compression and acceleration

(Unstructured) Weight Pruning via Adaptive Sparsity Loss

TensorFlow implementation of weight and unit pruning and sparsification

Sparsify Your Flux Models

TensorFlow implementation of weight and unit pruning and sparsification

Feather is a module that enables effective sparsification of neural networks during training. This repository accompanies the paper "Feather: An Elegant Solution to Effective DNN Sparsification" (BMVC2023).

A simple C++14 and CUDA-based header-only library with tools for sparse-machine learning.

An implementation and report of the twice Ramanujan graph sparsifiers.

The communication efficiency of federated learning is improved by sparsifying the parameters uploaded by the clients.

CS328 Introduction to Data Science - Prof. Anirban Dasgupta - Project: Sparsifying Networks while Preserving Properties