Alternatives and similar repositories for conformalized-gnn

Users that are interested in conformalized-gnn are comparing it to the libraries listed below

• XiaoxinHe / neurips2023_learning_on_graphs
  List of papers on NeurIPS2023
  ☆89Updated last year
• luis-mueller / probing-graph-transformers
  Code for our paper "Attending to Graph Transformers"
  ☆91Updated last year
• G-Taxonomy-Workgroup / GPSE
  Graph Positional and Structural Encoder
  ☆53Updated 9 months ago
• GraphFramEx / graphframex
  GraphFramEx: a systematic evaluation framework for explainability methods on GNNs
  ☆46Updated last year
• vijaydwivedi75 / lrgb
  Long Range Graph Benchmark, NeurIPS 2022 Track on D&B
  ☆160Updated last year
• ellisalicante / GraphRewiring-Tutorial
  This repository holds code and other relevant files for the Learning on Graphs 2022 tutorial "Graph Rewiring: From Theory to Applications…
  ☆54Updated 2 years ago
• wanyu-lin / ICML2021-Gem
  Official code for the ICML 2021 paper "Generative Causal Explanations for Graph Neural Networks."
  ☆68Updated 3 years ago
• chr26195 / PMLP
  This is the official code repository for "Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs".
  ☆90Updated 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
  ☆46Updated 4 years ago
• mims-harvard / GraphXAI
  GraphXAI: Resource to support the development and evaluation of GNN explainers
  ☆198Updated last year
• divelab / GOOD
  GOOD: A Graph Out-of-Distribution Benchmark [NeurIPS 2022 Datasets and Benchmarks]
  ☆202Updated 8 months ago
• jctops / understanding-oversquashing
  ☆42Updated 3 years ago
• XiaoxinHe / icml2023_learning_on_graphs
  List of papers on ICML2023.
  ☆55Updated 2 years ago
• Graph-COM / GSAT
  [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.
  ☆170Updated last year
• emalgorithm / directed-graph-neural-network
  Dir-GNN is a machine learning model that enables learning on directed graphs.
  ☆82Updated 2 years ago
• RexYing / Rex-Ying-Thesis
  Rex Ying's Ph.D. Thesis, Stanford University
  ☆41Updated 3 years ago
• BenGutteridge / DRew
  ☆31Updated last year
• twitter-research / feature-propagation
  ☆85Updated 3 years ago
• tk-rusch / gradientgating
  Gradient gating (ICLR 2023)
  ☆55Updated 2 years ago
• Wuyxin / ReFine
  Towards Multi-Grained Explainability for Graph Neural Networks (NeurIPS 2021) + Pytorch Implementation of GNN attribution methods
  ☆70Updated 8 months ago
• FilippoMB / The-expressive-power-of-pooling-in-GNNs
  Code and dataset to test empirically the expressive power of graph pooling operators presented as presented at NeurIPS 2023
  ☆36Updated last year
• iDEA-iSAIL-Lab-UIUC / pyg-ssl
  Graph Self-Supervised Learning Toolkit
  ☆43Updated 4 months ago
• CurryTang / Towards-graph-foundation-models
  ☆90Updated 2 years ago
• mengliu1998 / awesome-expressive-gnn
  A collection of papers studying/improving the expressiveness of graph neural networks (GNNs)
  ☆124Updated last year
• twitter-research / neural-sheaf-diffusion
  ☆80Updated 2 years ago
• stadlmax / Graph-Posterior-Network
  Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification (NeurIPS 2021)
  ☆44Updated 3 years ago
• beabevi / ESAN
  Equivariant Subgraph Aggregation Networks (ICLR 2022 Spotlight)
  ☆89Updated 2 years ago
• azminewasi / Awesome-Graph-Research-ICLR2024
  It is a comprehensive resource hub compiling all graph papers accepted at the International Conference on Learning Representations (ICLR)…
  ☆99Updated 11 months ago
• azminewasi / Awesome-Graph-Research-NeurIPS2024
  All graph/GNN papers accepted at NeurIPS 2024.
  ☆82Updated 11 months ago
• hypergraphlab / Hypergraph-Tutorial
  ☆61Updated last year