selkerdawy

deepsparse

Sparsity-aware deep learning inference runtime for CPUs

RSS-Interference-CVPRW2022

[CVPR EVW, 2022]Does Interference Exist When Training a Once-For-All Network?

bolt

10x faster matrix and vector operations

BNNAS

triton

Development repository for the Triton language and compiler

torch-blocksparse

Block-sparse primitives for PyTorch

SWALP

Code for paper "SWALP: Stochastic Weight Averaging forLow-Precision Training".

applied-ml

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

vit-pytorch

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

torchprune

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

LC-model-compression

Model compression by constrained optimization, using the Learning-Compression (LC) algorithm

models-comparison.pytorch

Code for the paper Benchmark Analysis of Representative Deep Neural Network Architectures

PlotNeuralNet

Latex code for making neural networks diagrams

EagleEye

(ECCV'2020 Oral)EagleEye: Fast Sub-net Evaluation for Efficient Neural Network Pruning

CompRess

Compressing Representations for Self-Supervised Learning

BLT

Balancing Long-Tailed Datasets with Adversarially-Perturbed Images (ACCV 2020)

WoodScape

The repository containing tools and information about the WoodScape dataset.

AutoDL-Projects

Automated deep learning algorithms implemented in PyTorch.

ml-design-patterns

Source code accompanying O'Reilly book: Machine Learning Design Patterns

pytorch-retinanet

RetinaNet in PyTorch

coral-cnn

Rank Consistent Ordinal Regression for Neural Networks with Application to Age Estimation

Hadamard-Matrix-for-hashing

CVPR2020/TNNLS2023: Central Similarity Quantization/Hashing for Efficient Image and Video Retrieval

DNNsim

slimmable_networks

Slimmable Networks, AutoSlim, and Beyond, ICLR 2019, and ICCV 2019

DeepShift

Implementation of "DeepShift: Towards Multiplication-Less Neural Networks" https://arxiv.org/abs/1905.13298

haq

[CVPR 2019, Oral] HAQ: Hardware-Aware Automated Quantization with Mixed Precision

AdderNet

Code for paper " AdderNet: Do We Really Need Multiplications in Deep Learning?"

filter-pruning-geometric-median

Filter Pruning via Geometric Median for Deep Convolutional Neural Networks Acceleration (CVPR 2019 Oral)

pytorch-self-distillation

netadapt

This repo contains the official Pytorch reimplementation of the paper "NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications".