xinleihe

pytorch-image-models

The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more

awesome-semi-supervised-learning

😎 An up-to-date & curated list of awesome semi-supervised learning papers, methods & resources.

google-images-download

Python Script to download hundreds of images from 'Google Images'. It is a ready-to-run code!

Easy-Graph

EasyGraph is an open-source network analysis library designed to cover advanced network processing methods. It includes functionalities for detecting structural hole spanners, network embedding, and various classic network analysis techniques.

solo-learn

solo-learn: a library of self-supervised methods for visual representation learning powered by Pytorch Lightning

deep-learning-project-template

Pytorch Lightning code guideline for conferences

hydra

Hydra is a framework for elegantly configuring complex applications

graph-adversarial-learning-literature

A curated list of adversarial attacks and defenses papers on graph-structured data.

ImageNet-Datasets-Downloader

ImageNet dataset downloader. Creates a custom dataset by specifying the required number of classes and images in a class.

shap

A game theoretic approach to explain the output of any machine learning model.

lightning-hydra-template

PyTorch Lightning + Hydra. A very user-friendly template for ML experimentation. ⚡🔥⚡

BadEncoder

dataset-distillation

Open-source code for paper "Dataset Distillation"

MMD-mixup-Defense

FixMatch-pytorch

Unofficial PyTorch implementation of "FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence"

graph-fraud-detection-papers

A curated list of graph-based fraud, anomaly, and outlier detection papers & resources

uda

Unsupervised Data Augmentation (UDA)

DIG

A library for graph deep learning research

DANN

pytorch implementation of Domain-Adversarial Training of Neural Networks

pytorch-lightning

Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.

graph-adversarial-learning-literature

IDGL

Code & data accompanying the NeurIPS 2020 paper "Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddings".

Python

All Algorithms implemented in Python

datasets

A repository of pretty cool datasets that I collected for network science and machine learning research.

Graph_Sampling

Graph Sampling is a python package containing various approaches which samples the original graph according to different sample sizes.

magic-python

Python 黑魔法手册

knowledge-distillation-pytorch

A PyTorch implementation for exploring deep and shallow knowledge distillation (KD) experiments with flexibility

opacus

Training PyTorch models with differential privacy

pyvacy

Differentially Private Optimization for PyTorch 👁🙅‍♀️

SupContrast

PyTorch implementation of "Supervised Contrastive Learning" (and SimCLR incidentally)