Hu, Weihua

17 publications

ICLR 2025 ContextGNN: Beyond Two-Tower Recommendation Systems Yiwen Yuan, Zecheng Zhang, Xinwei He, Akihiro Nitta, Weihua Hu, Manan Shah, Blaž Stojanovič, Shenyang Huang, Jan Eric Lenssen, Jure Leskovec, Matthias Fey

NeurIPS 2024 From Similarity to Superiority: Channel Clustering for Time Series Forecasting Jialin Chen, Jan Eric Lenssen, Aosong Feng, Weihua Hu, Matthias Fey, Leandros Tassiulas, Jure Leskovec, Rex Ying

ICML 2024 Position: Relational Deep Learning - Graph Representation Learning on Relational Databases Matthias Fey, Weihua Hu, Kexin Huang, Jan Eric Lenssen, Rishabh Ranjan, Joshua Robinson, Rex Ying, Jiaxuan You, Jure Leskovec

NeurIPSW 2024 PyTorch Frame: A Modular Framework for Multi-Modal Tabular Learning Weihua Hu, Yiwen Yuan, Zecheng Zhang, Akihiro Nitta, Kaidi Cao, Vid Kocijan, Jinu Sunil, Jure Leskovec, Matthias Fey

NeurIPS 2024 RelBench: A Benchmark for Deep Learning on Relational Databases Joshua Robinson, Rishabh Ranjan, Weihua Hu, Kexin Huang, Jiaqi Han, Alejandro Dobles, Matthias Fey, Jan E. Lenssen, Yiwen Yuan, Zecheng Zhang, Xinwei He, Jure Leskovec

NeurIPSW 2024 Relational Deep Learning: Graph Representation Learning on Relational Databases Joshua Robinson, Rishabh Ranjan, Weihua Hu, Kexin Huang, Jiaqi Han, Alejandro Dobles, Matthias Fey, Jan Eric Lenssen, Yiwen Yuan, Zecheng Zhang, Xinwei He, Jure Leskovec

NeurIPS 2023 Temporal Graph Benchmark for Machine Learning on Temporal Graphs Shenyang Huang, Farimah Poursafaei, Jacob Danovitch, Matthias Fey, Weihua Hu, Emanuele Rossi, Jure Leskovec, Michael Bronstein, Guillaume Rabusseau, Reihaneh Rabbany

ICLR 2022 Extending the WILDS Benchmark for Unsupervised Adaptation Shiori Sagawa, Pang Wei Koh, Tony Lee, Irena Gao, Sang Michael Xie, Kendrick Shen, Ananya Kumar, Weihua Hu, Michihiro Yasunaga, Henrik Marklund, Sara Beery, Etienne David, Ian Stavness, Wei Guo, Jure Leskovec, Kate Saenko, Tatsunori Hashimoto, Sergey Levine, Chelsea Finn, Percy Liang

NeurIPSW 2021 Extending the WILDS Benchmark for Unsupervised Adaptation Shiori Sagawa, Pang Wei Koh, Tony Lee, Irena Gao, Sang Michael Xie, Kendrick Shen, Ananya Kumar, Weihua Hu, Michihiro Yasunaga, Henrik Marklund, Sara Beery, Etienne David, Ian Stavness, Wei Guo, Jure Leskovec, Kate Saenko, Tatsunori Hashimoto, Sergey Levine, Chelsea Finn, Percy Liang

NeurIPS 2020 Open Graph Benchmark: Datasets for Machine Learning on Graphs Weihua Hu, Matthias Fey, Marinka Zitnik, Yuxiao Dong, Hongyu Ren, Bowen Liu, Michele Catasta, Jure Leskovec

ICLR 2020 Query2box: Reasoning over Knowledge Graphs in Vector Space Using Box Embeddings Hongyu Ren, Weihua Hu, Jure Leskovec

ICLR 2020 Strategies for Pre-Training Graph Neural Networks Weihua Hu, Bowen Liu, Joseph Gomes, Marinka Zitnik, Percy Liang, Vijay Pande, Jure Leskovec

ICLR 2019 How Powerful Are Graph Neural Networks? Keyulu Xu, Weihua Hu, Jure Leskovec, Stefanie Jegelka

NeurIPS 2018 Co-Teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels Bo Han, Quanming Yao, Xingrui Yu, Gang Niu, Miao Xu, Weihua Hu, Ivor Tsang, Masashi Sugiyama

ICML 2018 Does Distributionally Robust Supervised Learning Give Robust Classifiers? Weihua Hu, Gang Niu, Issei Sato, Masashi Sugiyama

ICML 2017 Learning Discrete Representations via Information Maximizing Self-Augmented Training Weihua Hu, Takeru Miyato, Seiya Tokui, Eiichi Matsumoto, Masashi Sugiyama

NeurIPS 2017 Learning from Complementary Labels Takashi Ishida, Gang Niu, Weihua Hu, Masashi Sugiyama