azminewasi / Awesome-Graph-Research-ICLR2024Links
It is a comprehensive resource hub compiling all graph papers accepted at the International Conference on Learning Representations (ICLR) in 2024.
☆98Updated 11 months ago
Alternatives and similar repositories for Awesome-Graph-Research-ICLR2024
Users that are interested in Awesome-Graph-Research-ICLR2024 are comparing it to the libraries listed below
Sorting:
- List of papers on NeurIPS2023☆89Updated last year
- All graph/GNN papers accepted at the International Conference on Machine Learning (ICML) 2024.☆224Updated 11 months ago
- Accompanied repositories for our paper Graph foundation model☆222Updated 11 months ago
- ☆90Updated 2 years ago
- A collection of papers on Graph Structural Learning (GSL)☆56Updated last year
- A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?☆120Updated 2 years ago
- A curated list of papers on pre-training for graph neural networks (Pre-train4GNN).☆207Updated 9 months ago
- Code for our paper "Attending to Graph Transformers"☆91Updated last year
- This is the official code repository for "Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs".☆90Updated last year
- A list for GNNs and related works.☆101Updated 3 months ago
- List of papers on ICLR 2024☆59Updated last year
- A comprehensive benchmark of Graph Structure Learning (NeurIPS 2023 Datasets and Benchmarks Track)☆120Updated last year
- This repository contains the resources on graph neural network (GNN) considering heterophily.☆263Updated 10 months ago
- [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.☆170Updated last year
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆86Updated 11 months ago
- Kolmogorov Arnold Networks (KANs) for Graph Neural Networks (GNNs) and Tasks on Graphs☆63Updated last year
- [IJCAI 2024] Papers about graph reduction including graph coarsening, graph condensation, graph sparsification, graph summarization, etc.☆167Updated 2 weeks ago
- A curated list of papers on graph structure learning (GSL).☆50Updated 9 months ago
- PyTorch implementation of "BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation"☆57Updated 2 years ago
- ☆58Updated last year
- Official Implementation of "D4Explainer: In-Distribution GNN Explanations via Discrete Denoising Diffusion"☆23Updated last year
- Official Implementation of ICML 2023 paper: "A Generalization of ViT/MLP-Mixer to Graphs"☆165Updated last year
- code for Graph Neural Networks for Link Prediction with Subgraph Sketching https://arxiv.org/abs/2209.15486☆96Updated last year
- Transformer-based Spectral Graph Neural Networks☆85Updated last year
- A collection of graph foundation models including papers, codes, and datasets.☆121Updated 3 months ago
- Main code for "Revisiting over-smoothing and over-squashing using the Ollivier-Ricci curvature" paper☆17Updated 2 years ago
- Awesome Temporal Graph Learning is a collection of SOTA, novel temporal graph learning methods (papers, codes, and datasets).☆80Updated 5 months ago
- Long Range Graph Benchmark, NeurIPS 2022 Track on D&B☆160Updated last year
- GOOD: A Graph Out-of-Distribution Benchmark [NeurIPS 2022 Datasets and Benchmarks]☆202Updated 8 months ago
- GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)☆32Updated last year