sethGu

sethGu's Stars

• yixinliu233/D2PT

  [KDD'23] Learning Strong Graph Neural Networks with Weak Information

  Language:Python423

• zhao-tong/GAug

  AAAI'21: Data Augmentation for Graph Neural Networks

  Language:Python18533

• sycny/GiGaMAE

  PyTorch implementation for 'GiGaMA: Generalizable Graph Masked Autoencoder via Collaborative Latent Space Reconstruction'

  Language:Python13

• kaize0409/awesome-few-shot-gnn

  An index of algorithms for few-shot learning/meta-learning on graphs

  12915

• facebookresearch/classifier-balancing

  This repository contains code for the paper "Decoupling Representation and Classifier for Long-Tailed Recognition", published at ICLR 2020

  Language:Python935131

• LFhase/CIGA

  [NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs

  Language:Python9710

• yixinliu233/G-OOD-D

  [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection

  Language:Python335

• LiLittleCat/awesome-free-chatgpt

  🆓免费的 ChatGPT 镜像网站列表，持续更新。List of free ChatGPT mirror sites, continuously updated.

  Language:Python17.6k1.2k

• HobbitLong/SupContrast

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

  Language:Python3k525

• yizhe-ang/AdaMatch-PyTorch

  Unofficial PyTorch Implementation of AdaMatch: A Unified Approach to Semi-Supervised Learning and Domain Adaptation

  Language:Python132

• yaoyao-liu/few-shot-classification-leaderboard

  Leaderboards for few-shot image classification on miniImageNet, tieredImageNet, FC100, and CIFAR-FS.

  Language:HTML38274

• Evgeneus/Graph-Domain-Adaptaion

  PyTorch code for the paper "Curriculum Graph Co-Teaching for Multi-target Domain Adaptation" (CVPR2021)

  Language:Python9818

• ShuoYang-1998/Few_Shot_Distribution_Calibration

  [ICLR2021 Oral] Free Lunch for Few-Shot Learning: Distribution Calibration

  Language:Python46971

• takeshi-teshima/few-shot-domain-adaptation-by-causal-mechanism-transfer

  Implementation of Few-shot Domain Adaptation by Causal Mechanism Transfer (ICML 2020)

  Language:Python3913

• yue-zhongqi/ifsl

  [NeurIPS 2020] Released code for Interventional Few-Shot Learning

  Language:Python16523

• roboticcam/machine-learning-notes

  My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (2000+ slides) 我不间断更新的机器学习，概率模型和深度学习的讲义(2000+页)和视频链接

  Language:Jupyter Notebook8.3k1.7k

• huaxiuyao/GFL

  GFL for AAAI 2020

  Language:Python314

• benedekrozemberczki/FEATHER

  The reference implementation of FEATHER from the CIKM '20 paper "Characteristic Functions on Graphs: Birds of a Feather, from Statistical Descriptors to Parametric Models".

  Language:Python4412

• benedekrozemberczki/karateclub

  Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)

  Language:Python2.1k245

• cleanlab/cleanlab

  The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

  Language:Python9.4k723

• lvjiaqi77/PRODEN

  Code for the paper "Progressive Identification of True Labels for Partial-Label Learning".

  Language:Python454

• Sean-Huang65/AUX-TS

  official code for our KDD21 paper "Adaptive Transfer Learning on Graph Neural Networks"

  Language:Python395

• ASKCOS/ASKCOS

  Software package for computer aided synthesis planning

  Language:Python20146

• cdarlint/winutils

  winutils.exe hadoop.dll and hdfs.dll binaries for hadoop windows

  Language:Shell1.9k2.1k

• TrustAGI-Lab/CoLA

  [TNNLS] Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning

  Language:Python7620

• XiaoxiaoMa-MQ/Awesome-Deep-Graph-Anomaly-Detection

  Awesome graph anomaly detection techniques built based on deep learning frameworks. Collections of commonly used datasets, papers as well as implementations are listed in this github repository. We also invite researchers interested in anomaly detection, graph representation learning, and graph anomaly detection to join this project as contributors and boost further research in this area.

  31248

• TianjinYellow/GAE-AT

  On Generalization of Graph Autoencoders with Adversarial Training[ECML2021]

  Language:Python2

• WangWenhao0716/DomainMix

  [BMVC 2021] The official implementation of "DomainMix: Learning Generalizable Person Re-Identification Without Human Annotations"

  Language:Python201

• LYuhang/GNN_Review

  GNN综述阅读报告

  Language:Jupyter Notebook865215

• thunlp/GNNPapers

  Must-read papers on graph neural networks (GNN)

  15.8k3k