DSL-Lab / Specformer
Transformer-based Spectral Graph Neural Networks
☆79Updated 5 months ago
Alternatives and similar repositories for Specformer:
Users that are interested in Specformer are comparing it to the libraries listed below
- [ICLR 2023] "Equivariant Hypergraph Diffusion Neural Operators" by Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li☆44Updated 7 months ago
- Official Implementation of ICML 2023 paper: "A Generalization of ViT/MLP-Mixer to Graphs"☆158Updated 11 months ago
- List of papers on NeurIPS2023☆89Updated last year
- This is the official code repository for "Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs", wh…☆87Updated 9 months ago
- PyTorch implementation of "BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation"☆53Updated last year
- Implementation for the paper: GraphGDP: Generative Diffusion Processes for Permutation Invariant Graph Generation☆26Updated 2 years ago
- NeurIPS'22 Spotlight paper "Hierarchical Graph Transformer with Adaptive Node Sampling"☆50Updated last year
- [ICLR 2023 notable top-5%] Rethinking the Expressive Power of GNNs via Graph Biconnectivity (official implementation)☆103Updated last year
- ☆87Updated last year
- Source code for From Stars to Subgraphs (ICLR 2022)☆68Updated 11 months ago
- A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?☆112Updated 2 years ago
- Unified Graph Transformer (UGT) is a novel Graph Transformer model specialised in preserving both local and global graph structures and d…☆27Updated 3 months ago
- [KDD 2023] What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders☆84Updated 4 months ago
- A collection of papers on Graph Structural Learning (GSL)☆54Updated last year
- Code and dataset to test empirically the expressive power of graph pooling operators presented as presented at NeurIPS 2023☆36Updated last year
- A comprehensive benchmark of Graph Structure Learning (NeurIPS 2023 Datasets and Benchmarks Track)☆112Updated last year
- Code for our paper "Attending to Graph Transformers"☆85Updated last year
- EDGE: Efficient and Degree-Guided Graph Generation via Discrete Diffusion Modeling☆55Updated last year
- ☆51Updated 4 months ago
- A curated list of papers on graph structure learning (GSL).☆45Updated 2 months ago
- It is a comprehensive resource hub compiling all graph papers accepted at the International Conference on Learning Representations (ICLR)…☆87Updated 4 months ago
- [ICLR 2024] VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs☆93Updated last year
- Dynamic Graph Benchmark☆74Updated 2 years ago
- ☆30Updated last year
- ☆53Updated 2 years ago
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆101Updated 2 years ago
- The code repository of "Towards Deep Attention in Graph Neural Networks: Problems and Remedies," published in ICML 2023.☆28Updated 9 months ago
- This is an official implementation for "GRIT: Graph Inductive Biases in Transformers without Message Passing".☆117Updated 3 months ago
- Main code for "Revisiting over-smoothing and over-squashing using the Ollivier-Ricci curvature" paper☆16Updated last year
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆75Updated 4 months ago