THUMNLab / awesome-auto-graph-learningLinks
A paper collection about automated graph learning
☆96Updated last year
Alternatives and similar repositories for awesome-auto-graph-learning
Users that are interested in awesome-auto-graph-learning are comparing it to the libraries listed below
Sorting:
- Papers about out-of-distribution generalization on graphs.☆166Updated 2 years ago
- Schedule for learning on graphs seminar☆109Updated last year
- ☆135Updated last year
- How Powerful are Spectral Graph Neural Networks☆72Updated last year
- Learning to Drop: Robust Graph Neural Network via Topological Denoising & Robust Graph Representation Learning via Neural Sparsification☆80Updated 4 years ago
- The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"☆89Updated 2 years ago
- Source code for WWW 2021 paper "Graph Structure Estimation Neural Networks"☆58Updated 3 years ago
- Bag of Tricks for Graph Neural Networks.☆295Updated 11 months ago
- PyTorch implementation of "BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation"☆54Updated 2 years ago
- Awesome literature on imbalanced learning on graphs☆76Updated 9 months ago
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆103Updated last week
- ☆138Updated last year
- [ICLR'22] [KDD'22] [IJCAI'24] Implementation of "Graph Condensation for Graph Neural Networks"☆138Updated 7 months ago
- AAAI'21: Data Augmentation for Graph Neural Networks☆193Updated last year
- Advances on machine learning of dynamic (temporal) graphs, covering the reading list of recent top academic conferences.☆61Updated last year
- This is the GitHub repository for our ICLR22 paper: "You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks"☆98Updated last year
- ☆76Updated 3 years ago
- NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs☆125Updated last year
- A fundational graph learning framework that solves cross-domain/cross-task classification problems using one model.☆221Updated last year
- The official code of WWW2021 paper: Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation …☆77Updated 3 years ago
- Discovering Invariant Rationales for Graph Neural Networks (ICLR 2022)☆127Updated last year
- NeurIPS'22 Spotlight paper "Hierarchical Graph Transformer with Adaptive Node Sampling"☆51Updated last year
- This is the official code repository for "Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs", wh…☆88Updated last year
- Source code for NeurIPS 2022 paper "Uncovering the Structural Fairness in Graph Contrastive Learning"☆29Updated 2 years ago
- ☆13Updated 3 years ago
- ☆100Updated last year
- A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?☆119Updated 2 years ago
- Node Dependent Local Smoothing for Scalable Graph Learning (NeurIPS'21, Spotlight)☆21Updated 3 years ago
- A comprehensive benchmark of Graph Structure Learning (NeurIPS 2023 Datasets and Benchmarks Track)☆116Updated last year
- ☆76Updated 2 years ago