ege-erdogan / awesome-weight-space-learning
Awesome papers on weight-space learning
☆12Updated this week
Alternatives and similar repositories for awesome-weight-space-learning:
Users that are interested in awesome-weight-space-learning are comparing it to the libraries listed below
- Python implementation of Scaling Neural Tangent Kernels via Sketching and Random Features☆13Updated 3 years ago
- Learning Graphons via Structured Gromov-Wasserstein Barycenters☆22Updated 4 years ago
- List of papers on NeurIPS2023☆89Updated last year
- ☆9Updated 2 years ago
- New structural distributional shifts for evaluating graph models☆17Updated last year
- Official implementation of GOAT model (ICML2023)☆37Updated last year
- Official source code for "Graph Neural Networks for Learning Equivariant Representations of Neural Networks". In ICLR 2024 (oral).☆78Updated 8 months ago
- Graph Neural Convection-Diffusion with Heterophily☆11Updated last year
- A python package providing a benchmark with various specified distribution shift patterns.☆57Updated last year
- ☆13Updated 3 months ago
- Neural Tangent Kernel Papers☆108Updated 2 months ago
- EDGE: Efficient and Degree-Guided Graph Generation via Discrete Diffusion Modeling☆55Updated last year
- Code and dataset to test empirically the expressive power of graph pooling operators presented as presented at NeurIPS 2023☆37Updated last year
- Adaptive evaluation reveals that most examined adversarial defenses for GNNs show no or only marginal improvement in robustness. (NeurIPS…☆29Updated 2 years ago
- List of papers on ICML2023.☆55Updated last year
- ☆40Updated 2 years ago
- Welcome to the 'In Context Learning Theory' Reading Group☆28Updated 4 months ago
- Official implementation for 'Sparse denoising diffusion for large graph generation'☆57Updated 10 months ago
- Official implementation for the paper: Permutation Invariant Graph Generation via Score-Based Generative Modeling☆110Updated last year
- How Powerful are Spectral Graph Neural Networks☆71Updated last year
- Reference implementation for SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generators (ICML …☆26Updated 2 years ago
- Open-source Library PyGDebias: Graph Datasets and Fairness-Aware Graph Mining Algorithms☆63Updated 10 months ago
- This repository contains the official implementation of the paper "Robustness of Graph Neural Networks at Scale" (NeurIPS, 2021).☆30Updated last year
- The code for the ICML 2021 paper "Graph Neural Networks Inspired by Classical Iterative Algorithms".☆43Updated 3 years ago
- ☆34Updated last year
- [WWW 2021 GLB] New Benchmarks for Learning on Non-Homophilous Graphs☆112Updated 3 years ago
- [ICML 2023] Structural Re-weighting Improves Graph Domain Adaptation (StruRW)☆21Updated last year
- ☆23Updated 4 years ago
- The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"☆86Updated 2 years ago
- ☆26Updated 2 weeks ago