HongtengXu / Reading-ListLinks
A list of papers for group meeting
☆16Updated 2 months ago
Alternatives and similar repositories for Reading-List
Users that are interested in Reading-List are comparing it to the libraries listed below
Sorting:
- [ICLR 2023] "Graph Domain Adaptation via Theory-Grounded Spectral Regularization" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen☆22Updated 2 years ago
- [AAAI2023 Oral] The official implementation of "Hierarchical Contrastive Learning for Temporal Point Processes"☆26Updated 4 months ago
- ☆11Updated 2 years ago
- [ICLR 2023] Learnable Randomness Injection (LRI) for interpretable Geometric Deep Learning.☆23Updated 2 years ago
- A Quasi-Wasserstein Loss for Learning Graph Neural Networks (QW loss)☆10Updated last year
- "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')☆48Updated 3 years ago
- [NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs☆116Updated last year
- The code for the ICML 2021 paper "Graph Neural Networks Inspired by Classical Iterative Algorithms".☆43Updated 4 years ago
- This is the official codebase of `Exploring Generative Neural Temporal Point Process' (Accepted by TMLR).☆19Updated 2 years ago
- Diffusion Models for Graphs Benefit From Discrete State Spaces☆34Updated 2 years ago
- ☆14Updated 3 years ago
- [ICML 2022] pGNN, p-Laplacian Based Graph Neural Networks☆27Updated 3 years ago
- A curated list of resources for OOD detection with graph data.☆19Updated last year
- Papers about developing DL methods on disassortative graphs☆48Updated 3 years ago
- Ratioanle-aware Graph Contrastive Learning codebase☆44Updated 2 years ago
- ☆16Updated last year
- Code for Online Graph Dictionary Learning☆17Updated 3 years ago
- GOOD: A Graph Out-of-Distribution Benchmark [NeurIPS 2022 Datasets and Benchmarks]☆200Updated 5 months ago
- Official implementation of the ICML2021 paper "Elastic Graph Neural Networks"☆42Updated 4 years ago
- Size-Invariant Graph Representations for Graph Classification Extrapolations (ICML 2021 Long Talk)☆23Updated 2 years ago
- Learnable Global Pooling Layers Based on Regularized Optimal Transport (ROT)☆16Updated last year
- Reading list of papers (basically are conference papers) about homophily and heterophily in GNNs.☆9Updated 2 years ago
- The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021☆36Updated 3 years ago
- Official implementation for GraphDE: A Generative Framework for Debiased Learning and Out-of-Distribution Detection on Graphs (NeurIPS 20…☆20Updated 2 years ago
- GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)☆31Updated last year
- [WWW2022] Geometric Graph Representation Learning via Maximizing Rate Reduction☆27Updated 3 years ago
- Variational Graph Convolutional Networks☆23Updated 4 years ago
- NeurIPS'22 Oral: EquiVSet - Learning Neural Set Functions Under the Optimal Subset Oracle☆20Updated 2 years ago
- Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization (NeurIPS 21')☆23Updated 3 years ago
- [ICML 2023] Structural Re-weighting Improves Graph Domain Adaptation (StruRW)☆21Updated 2 years ago