CANDY404

CANDY404's Stars

• dmlc/dgl

  Python package built to ease deep learning on graph, on top of existing DL frameworks.

  Language:Python13.4k1722.8k3k

• naturomics/CapsNet-Tensorflow

  A Tensorflow implementation of CapsNet(Capsules Net) in paper Dynamic Routing Between Capsules

  Language:Python3.8k249661.2k

• microsoft/Graphormer

  Graphormer is a general-purpose deep learning backbone for molecular modeling.

  Language:Python2.1k31151333

• benedekrozemberczki/CapsGNN

  A PyTorch implementation of "Capsule Graph Neural Network" (ICLR 2019).

  Language:Python1.2k2920197

• weihua916/powerful-gnns

  How Powerful are Graph Neural Networks?

  Language:Python1.2k2623222

• YyzHarry/imbalanced-regression

  [ICML 2021, Long Talk] Delving into Deep Imbalanced Regression

  Language:Python8061944128

• AstraZeneca/chemicalx

  A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022)

  Language:Python706224388

• HazyResearch/hgcn

  Hyperbolic Graph Convolutional Networks in PyTorch.

  Language:Python5862648107

• gasteigerjo/ppnp

  PPNP & APPNP models from "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019)

  Language:Jupyter Notebook317101654

• tech-srl/how_attentive_are_gats

  Code for the paper "How Attentive are Graph Attention Networks?" (ICLR'2022)

  Language:Python29911738

• shuxinyin/NLP-Loss-Pytorch

  Implementation of some unbalanced loss like focal_loss, dice_loss, DSC Loss, GHM Loss et.al

  Language:Python2494544

• wujcan/SGL-TensorFlow

  Language:Python17333543

• Graph-COM/GSAT

  [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.

  Language:Jupyter Notebook15641219

• Christian-lyc/NAM

  Language:Python15131320

• logseminar/Schedule

  Schedule for learning on graphs seminar

  1101105

• PonderLY/PC-GNN

  (WWW 2021) Source code of PC-GNN

  Language:Python9511021

• BorealisAI/SLAPS-GNN

  PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"

  Language:Python856214

• hengruizhang98/CCA-SSG

  Codes for 'From Canonical Correlation Analysis to Self-supervised Graph Neural Networks'. https://arxiv.org/abs/2106.12484

  Language:Python68177

• datake/AdaGCN

  Official Implementation of AdaGCN (ICLR 2021)

  Language:Python604512

• amazon-science/gnn-tail-generalization

  Language:Python528414

• GentleZhu/Shift-Robust-GNNs

  "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')

  Language:Python47447

• ZulunZhu/SpikingGCN

  Language:Jupyter Notebook39229

• hedongxiao-tju/HOG-GCN

  Language:Gherkin37219

• jindi-tju/HGNN-AC

  Source code of "WWW21 - Heterogeneous Graph Neural Network via Attribute Completion"

  Language:Python371110

• wyl7/DCI-pytorch

  The pytorch implementation of DCI (SIGIR2021).

  Language:Python35139

• hedongxiao-tju/BM-GCN

  The code of paper "Block Modeling-Guided Graph Convolutional Neural Networks".

  Language:Python31227

• mobvistaresearch/CIKM2020-BotSpot

  Language:Python8104

• arcsysu/arcsysu.github.io

  Language:HTML5401

• dleyan/MDGCN

  Markov-Driven Graph Convolutional Networksfor Social Spammer Detection

  Language:Python5202

• mobvistaresearch/BotSpot-Plus

  The enhance version of BotSpot

  Language:Python4114