Weilin Cong

6 papers · 2020–2025 · 3 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

Jump to papers ↓

🌍 Conference Polyglot · Bronze 🏃 Academic Marathon · Sprint 🗺️ Taxonomy Completionist (11) 🐣 Hot Topic Early Bird ❓ The Questioner

Venues

ICLR (3) NeurIPS (2) AISTATS (1)

Top co-authors

Mehrdad Mahdavi (5) Morteza Ramezani (3) Mahmut Kandemir (2) Hao Wu (2) Si Zhang (2) Anand Sivasubramaniam (2) Baichuan Yuan (2) Bo Long (1) Hanghang Tong (1) Dongqi Fu (1)

Research topics

Deep Learning (6) Architectures (6) Machine Learning (4) Application Areas (2) Learning Types (2) Techniques (2) Artificial Intelligence (1) Learning Paradigms (1) Optimization & Theory (1)

Keywords

graph neural network (3) graph convolutional network (2) self-supervised learning (1) graph representation learning (1) convergence analysis (1) distributed learning (1) model architecture (1) machine unlearning (1) vector quantization (1) communication efficiency (1) model averaging (1) graph transformer (1) generalization capability (1) temporal graph (1) node feature (1) sampling method (1) gpu acceleration (1) feature propagation (1) hierarchical tokenization (1) model parameter projection (1)

Papers

Learning Graph Quantized Tokenizers ICLR 2025 Do We Really Need Complicated Model Architectures For Temporal Networks? ICLR 2023 Efficiently Forgetting What You Have Learned in Graph Representation Learning via Projection AISTATS 2023 Learn Locally, Correct Globally: A Distributed Algorithm for Training Graph Neural Networks ICLR 2022 On Provable Benefits of Depth in Training Graph Convolutional Networks NeurIPS 2021 GCN meets GPU: Decoupling “When to Sample” from “How to Sample” NeurIPS 2020