guoji-fu / MLT-PapersLinks
Awesome papers in machine learning theory
☆11Updated 3 years ago
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- The code for the ICML 2021 paper "Graph Neural Networks Inspired by Classical Iterative Algorithms".☆43Updated 4 years ago
- [ICML 2022] pGNN, p-Laplacian Based Graph Neural Networks☆27Updated 2 years ago
- Official code for the CVPR 2022 (oral) paper "OrphicX: A Causality-Inspired Latent Variable Model for Interpreting Graph Neural Networks.…☆34Updated 3 years ago
- NeurIPS'22 Oral: EquiVSet - Learning Neural Set Functions Under the Optimal Subset Oracle☆19Updated 2 years ago
- [ICML 2024] How Interpretable Are Interpretable Graph Neural Networks?☆12Updated 11 months ago
- Rethinking Graph Regularization for Graph Neural Networks (AAAI2021)☆34Updated 4 years ago
- [ICLR 2023] MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization☆77Updated 2 years ago
- Rex Ying's Ph.D. Thesis, Stanford University☆42Updated 2 years ago
- Implementation of the paper "Certifiable Robustness and Robust Training for Graph Convolutional Networks".☆43Updated 4 years ago
- Official code for the ICML 2021 paper "Generative Causal Explanations for Graph Neural Networks."☆66Updated 3 years ago
- ☆12Updated 2 years ago
- Official implementation of our VQ-GNN paper (NeurIPS2021)☆38Updated 3 years ago
- The official implementation of DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks (NeurIPS 2021)☆26Updated 2 years ago
- Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification (NeurIPS 2021)☆43Updated 2 years ago
- Variational Graph Convolutional Networks☆23Updated 4 years ago
- Code for the paper "SizeShiftReg: a Regularization Method for Improving Size-Generalization in Graph Neural Networks"☆12Updated 2 years ago
- Code for "Explainability methods for graph convolutional neural networks" - PE Pope*, S Kolouri*, M Rostami, CE Martin, H Hoffmann (CVPR …☆34Updated 2 months ago
- Official implementation of GOAT model (ICML2023)☆37Updated last year
- Code of "Breaking the Limits of Message Passing Graph Neural Networks" paper published in ICML2021☆41Updated 3 years ago
- Implementation of the paper "A New Perspective on the Effects of Spectrum in Graph Neural Networks"☆17Updated 2 years ago
- [ICML 2024] Code for Pairwise Alignment Improves Graph Domain Adaptation (Pair-Align)☆13Updated 11 months ago
- Uncertainty Aware Semi-Supervised Learning on Graph Data☆40Updated 4 years ago
- The official implementation of ''Can Graph Neural Networks Count Substructures?'' NeurIPS 2020☆34Updated 4 years ago
- Code for our ICML 2024 paper "Aligning Transformers with Weisfeiler-Leman"☆10Updated last year
- Source code for PairNorm (ICLR 2020)☆78Updated 5 years ago
- "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')☆48Updated 3 years ago
- [TPAMI 2022] "Bag of Tricks for Training Deeper Graph Neural Networks A Comprehensive Benchmark Study" by Tianlong Chen*, Kaixiong Zhou*,…☆125Updated 3 years ago
- This is an authors' implementation of the NIPS 2022 dataset and Benchmark Track Paper "A Comprehensive Study on Large Scale Graph Trainin…☆65Updated 2 years ago
- Code of "Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective" paper published in ICLR2021☆46Updated 3 years ago
- A collection of papers and resources about Data Centric Graph Machine Learning (DC-GML)☆37Updated last year