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Weihua Hu

13 papers · 2016–2025 · 4 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

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+5 more ↓ πŸŒ‰ Interdisciplinary Bridge Β· Silver πŸ—ΊοΈ Taxonomy Completionist (18) 🌍 Conference Polyglot Β· Bronze 🐣 Hot Topic Early Bird πŸƒ Academic Marathon Β· Sprint
πŸ‘₯ Mega-Team Β· Squad ❓ The Questioner πŸ”₯ Unstoppable Β· Bronze πŸ’Ž Century Club Β· Bronze πŸ—ƒοΈ Keyword Collector (52)

Venues

NeurIPS (6) ICML (4) ICLR (2) ACL (1)

Top co-authors

Jure Leskovec (8) Matthias Fey (6) Masashi Sugiyama (4) Jan Eric Lenssen (3) Gang Niu (3) Wei Guo (2) Henrik Marklund (2) Michihiro Yasunaga (2) Rishabh Ranjan (2) Xinwei He (2)

Research topics

Machine Learning (11) Core Methods (9) Application Areas (6) Data Science & Analytics (4) Deep Learning (4) Architectures (4) Learning Types (4) Methods (3) Applications (2) Knowledge & Reasoning (1) Mathematics & Optimization (1) Mathematics (1) Optimization & Theory (1) Representation (1)

Keywords

graph neural network (4) link prediction (4) distribution shift (3) feature engineering (2) unsupervised learning (2) domain adaptation (2) benchmark dataset (2) relational database (2) node classification (2) weakly supervised learning (1) time series forecasting (1) graph embedding (1) multi-class classification (1) graph representation learning (1) label noise (1) predictive modeling (1) deep neural network (1) knowledge graph (1) out-of-distribution generalization (1) risk estimation (1)

Papers

ContextGNN: Beyond Two-Tower Recommendation Systems ICLR 2025 From Similarity to Superiority: Channel Clustering for Time Series Forecasting NeurIPS 2024 Position: Relational Deep Learning - Graph Representation Learning on Relational Databases ICML 2024 RelBench: A Benchmark for Deep Learning on Relational Databases NeurIPS 2024 Temporal Graph Benchmark for Machine Learning on Temporal Graphs NeurIPS 2023 Extending the WILDS Benchmark for Unsupervised Adaptation ICLR 2022 WILDS: A Benchmark of in-the-Wild Distribution Shifts ICML 2021 Open Graph Benchmark: Datasets for Machine Learning on Graphs NeurIPS 2020 Co-teaching: Robust training of deep neural networks with extremely noisy labels NeurIPS 2018 Does Distributionally Robust Supervised Learning Give Robust Classifiers? ICML 2018 Learning Discrete Representations via Information Maximizing Self-Augmented Training ICML 2017 Learning from Complementary Labels NeurIPS 2017 A Latent Concept Topic Model for Robust Topic Inference Using Word Embeddings ACL 2016