LukeLIN-web / blogsLinks
My learning notes for ML&SYS.
☆13Updated last week
Alternatives and similar repositories for blogs
Users that are interested in blogs are comparing it to the libraries listed below
Sorting:
- ☆138Updated 2 years ago
- A scalable graph learning toolkit for extremely large graph datasets. (WWW'22, 🏆 Best Student Paper Award)☆157Updated last year
- The code of paper LMC: Fast Training of GNNs via Subgraph Sampling with Provable Convergence. Zhihao Shi, Xize Liang, Jie Wang. ICLR 2023…☆47Updated 2 years ago
- Schedule for learning on graphs seminar☆109Updated 2 years ago
- NeurIPS'22 Spotlight paper "Hierarchical Graph Transformer with Adaptive Node Sampling"☆52Updated 2 years ago
- A multi-backend graph learning library.☆243Updated 4 months ago
- NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs☆132Updated last year
- Largest realworld open-source graph dataset - Worked done under IBM-Illinois Discovery Accelerator Institute and Amazon Research Awards a…☆85Updated 5 months ago
- A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?☆121Updated 2 years ago
- The official implementation of the paper "Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing" (ICLR 2023).☆47Updated last year
- ☆59Updated last year
- Papers about out-of-distribution generalization on graphs.☆168Updated 2 years ago
- Long-range Meta-path Search through Progressive Sampling on Large-scale Heterogeneous Information Networks☆17Updated last year
- Code of GAMLP for Open Graph Benchmark. KDD‘22☆63Updated 3 years ago
- Must-read papers on graph foundation models (GFMs)☆356Updated 3 months ago
- Pytorch implementation of EvenNet.☆20Updated 3 years ago
- [NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods☆124Updated 3 years ago
- ☆29Updated 4 years ago
- ☆14Updated 4 years ago
- A paper collection about automated graph learning☆97Updated last year
- PyTorch implementation of "PolyGCL: GRAPH CONTRASTIVE LEARNING via Learnable Spectral Polynomial Filters"☆15Updated last year
- A PyTorch implementation of "Can Large Language Models Improve the Adversarial Robustness of Graph Neural Networks?" (KDD 2025)☆29Updated last month
- PyTorch implementation of "BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation"☆58Updated 2 years ago
- Node Dependent Local Smoothing for Scalable Graph Learning (NeurIPS'21, Spotlight)☆22Updated 3 years ago
- ☆22Updated 3 years ago
- It is a comprehensive resource hub compiling all graph papers accepted at the International Conference on Learning Representations (ICLR)…☆101Updated last year
- Toolkit for generating graphs and evaluating graph generators.☆16Updated 2 years ago
- The official implement of SIGKDD'24 paper: ZeroG: Investigating Cross-dataset Zero-shot Transferability in Graphs☆34Updated last year
- Advances on machine learning of dynamic (temporal) graphs, covering the reading list of recent top academic conferences.☆63Updated 2 years ago
- A Library for Dynamic Graph Learning (NeurIPS 2023)☆276Updated 2 years ago