Alternatives and similar repositories for NAS-Bench-Graph:

Users that are interested in NAS-Bench-Graph are comparing it to the libraries listed below

• LARS-research / PAS
  The released code for the paper: Pooling Architecture Search for Graph Classification, in CIKM 2021.
  ☆26Updated 3 years ago
• Kaixiong-Zhou / DGN
  Pytorch implementation of differentiable group normalization (NeurIPS 2020)
  ☆37Updated 4 years ago
• BorealisAI / SLAPS-GNN
  PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"
  ☆87Updated 3 years ago
• snap-research / graphless-neural-networks
  [ICLR 2022] Code for Graph-less Neural Networks: Teaching Old MLPs New Tricks via Distillation (GLNN)
  ☆88Updated 3 months ago
• snap-research / MLPInit-for-GNNs
  [ICLR 2023] MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization
  ☆77Updated last year
• ChandlerBang / GTrans
  [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"
  ☆56Updated last year
• nerdslab / bgrl
  PyTorch implementation of BGRL (https://arxiv.org/abs/2102.06514)
  ☆81Updated last year
• Graph-COM / PEG
  ☆38Updated last year
• VITA-Group / Unified-LTH-GNN
  [ICML 2021] "A Unified Lottery Tickets Hypothesis for Graph Neural Networks", Tianlong Chen*, Yongduo Sui*, Xuxi Chen, Aston Zhang, Zhang…
  ☆65Updated last year
• FFTYYY / TWIRLS
  The code for the ICML 2021 paper "Graph Neural Networks Inspired by Classical Iterative Algorithms".
  ☆43Updated 3 years ago
• GemsLab / H2GCN
  Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)
  ☆101Updated 2 years ago
• THUMNLab / awesome-auto-graph-learning
  A paper collection about automated graph learning
  ☆98Updated 7 months ago
• LARS-research / SANE
  The released code for the paper: Search to aggregate neighborhood for graph neural network, in ICDE 2021.
  ☆21Updated 2 years ago
• LFhase / CIGA
  [NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs
  ☆105Updated last year
• balcilar / gnn-spectral-expressive-power
  Code of "Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective" paper published in ICLR2021
  ☆45Updated 3 years ago
• zaixizhang / ANS-GT
  NeurIPS'22 Spotlight paper "Hierarchical Graph Transformer with Adaptive Node Sampling"
  ☆49Updated last year
• KarolisMart / DropGNN
  The official implementation of DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks (NeurIPS 2021)
  ☆25Updated 2 years ago
• zaixizhang / ProtGNN
  Official implementation of AAAI'22 paper "ProtGNN: Towards Self-Explaining Graph Neural Networks"
  ☆50Updated 2 years ago
• Namkyeong / BGRL_Pytorch
  Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"
  ☆78Updated 3 years ago
• xiangwang1223 / reinforced_causal_explainer
  Reinforced Causal Explainer for Graph Neural Networks, TPAMI2022
  ☆33Updated 2 years ago
• ChandlerBang / DeCorr
  [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"
  ☆45Updated last year
• ChandlerBang / AutoSSL
  [ICLR 2022] Implementation of paper "Automated Self-Supervised Learning for Graphs"
  ☆41Updated 2 years ago
• qslim / gnn-spectrum
  Implementation of the paper "A New Perspective on the Effects of Spectrum in Graph Neural Networks"
  ☆17Updated 2 years ago
• balcilar / gnn-matlang
  Code of "Breaking the Limits of Message Passing Graph Neural Networks" paper published in ICML2021
  ☆40Updated 3 years ago
• qwerfdsaplking / Graph-Trans
  A graph transformer framework
  ☆78Updated 2 years ago
• shyam196 / egc
  "Do We Need Anisotropic Graph Neural Networks?" at ICLR 2022
  ☆31Updated 2 years ago
• chr26195 / PMLP
  This is the official code repository for "Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs", wh…
  ☆86Updated 8 months ago
• ChandlerBang / GCond
  [ICLR'22] [KDD'22] [IJCAI'24] Implementation of "Graph Condensation for Graph Neural Networks"
  ☆134Updated 2 months ago
• Kaixiong-Zhou / EGNN
  Energetic GraphNeural Networks (EGNN) implementation based on Dirichlet Energy Constrained Learning.
  ☆24Updated 3 years ago
• lgalke / lifelong-learning
  Lifelong Learning of Graph Neural Networks for Open-World Node Classification
  ☆29Updated last year