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2020 – today
- 2024
[j9]Shiyao Xie, Wenjing Zhao, Guanghui Deng, Guohua He, Na He, Zhenhua Lu, Weihua Hu, Mingming Zhao, Jian Du
:
Utilizing ChatGPT as a scientific reasoning engine to differentiate conflicting evidence and summarize challenges in controversial clinical questions. J. Am. Medical Informatics Assoc. 31(7): 1551-1560 (2024)- [c33]Matthias Fey, Weihua Hu, Kexin Huang, Jan Eric Lenssen, Rishabh Ranjan, Joshua Robinson, Rex Ying, Jiaxuan You, Jure Leskovec:
Position: Relational Deep Learning - Graph Representation Learning on Relational Databases. ICML 2024 - [i22]Weihua Hu, Yiwen Yuan, Zecheng Zhang, Akihiro Nitta, Kaidi Cao, Vid Kocijan, Jure Leskovec, Matthias Fey:
PyTorch Frame: A Modular Framework for Multi-Modal Tabular Learning. CoRR abs/2404.00776 (2024) - [i21]Jialin Chen, Jan Eric Lenssen, Aosong Feng, Weihua Hu, Matthias Fey, Leandros Tassiulas, Jure Leskovec, Rex Ying:
From Similarity to Superiority: Channel Clustering for Time Series Forecasting. CoRR abs/2404.01340 (2024) - [i20]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:
RelBench: A Benchmark for Deep Learning on Relational Databases. CoRR abs/2407.20060 (2024) - 2023
- [c32]Shenyang Huang, Farimah Poursafaei, Jacob Danovitch, Matthias Fey, Weihua Hu, Emanuele Rossi, Jure Leskovec, Michael M. Bronstein, Guillaume Rabusseau, Reihaneh Rabbany:
Temporal Graph Benchmark for Machine Learning on Temporal Graphs. NeurIPS 2023 - [i19]Shenyang Huang, Farimah Poursafaei, Jacob Danovitch, Matthias Fey, Weihua Hu, Emanuele Rossi, Jure Leskovec, Michael M. Bronstein, Guillaume Rabusseau, Reihaneh Rabbany:
Temporal Graph Benchmark for Machine Learning on Temporal Graphs. CoRR abs/2307.01026 (2023) - [i18]Matthias Fey, Weihua Hu, Kexin Huang, Jan Eric Lenssen, Rishabh Ranjan, Joshua Robinson, Rex Ying, Jiaxuan You, Jure Leskovec:
Relational Deep Learning: Graph Representation Learning on Relational Databases. CoRR abs/2312.04615 (2023) - 2022
- [j8]Weihua Hu, Tao Wang, Yangsai Wang, Ziyang Chen, Guoheng Huang:
LE-MSFE-DDNet: a defect detection network based on low-light enhancement and multi-scale feature extraction. Vis. Comput. 38(11): 3731-3745 (2022) - [c31]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:
Extending the WILDS Benchmark for Unsupervised Adaptation. ICLR 2022 - [c30]Weihua Hu, Rajas Bansal, Kaidi Cao, Nikhil Rao, Karthik Subbian, Jure Leskovec:
Learning Backward Compatible Embeddings. KDD 2022: 3018-3028 - [i17]Weihua Hu, Rajas Bansal, Kaidi Cao, Nikhil Rao, Karthik Subbian, Jure Leskovec:
Learning Backward Compatible Embeddings. CoRR abs/2206.03040 (2022) - [i16]Weihua Hu, Kaidi Cao, Kexin Huang, Edward W. Huang, Karthik Subbian, Jure Leskovec:
TuneUp: A Training Strategy for Improving Generalization of Graph Neural Networks. CoRR abs/2210.14843 (2022) - [i15]Rémi Lam, Alvaro Sanchez-Gonzalez, Matthew Willson, Peter Wirnsberger, Meire Fortunato, Alexander Pritzel, Suman V. Ravuri, Timo Ewalds, Ferran Alet, Zach Eaton-Rosen, Weihua Hu, Alexander Merose, Stephan Hoyer, George Holland, Jacklynn Stott, Oriol Vinyals, Shakir Mohamed, Peter W. Battaglia:
GraphCast: Learning skillful medium-range global weather forecasting. CoRR abs/2212.12794 (2022) - 2021
- [c29]Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Irena Gao, Tony Lee, Etienne David, Ian Stavness, Wei Guo, Berton Earnshaw, Imran S. Haque, Sara M. Beery, Jure Leskovec, Anshul Kundaje, Emma Pierson, Sergey Levine, Chelsea Finn, Percy Liang:
WILDS: A Benchmark of in-the-Wild Distribution Shifts. ICML 2021: 5637-5664 - [c28]Weihua Hu, Matthias Fey, Hongyu Ren, Maho Nakata, Yuxiao Dong, Jure Leskovec:
OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs. NeurIPS Datasets and Benchmarks 2021 - [i14]Weihua Hu, Muhammed Shuaibi, Abhishek Das, Siddharth Goyal, Anuroop Sriram, Jure Leskovec, Devi Parikh, C. Lawrence Zitnick:
ForceNet: A Graph Neural Network for Large-Scale Quantum Calculations. CoRR abs/2103.01436 (2021) - [i13]Weihua Hu, Matthias Fey, Hongyu Ren, Maho Nakata, Yuxiao Dong, Jure Leskovec:
OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs. CoRR abs/2103.09430 (2021) - [i12]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:
Extending the WILDS Benchmark for Unsupervised Adaptation. CoRR abs/2112.05090 (2021) - 2020
- [c27]Zhongbai Jiang, Yanwei Sun, Lei Shi, Weihua Hu, Zhaohui Liu:
Secure Data Dissemination among Multiple Base Stations in High-Speed Railway Network. DSC 2020: 113-119 - [c26]Weihua Hu, Bowen Liu, Joseph Gomes, Marinka Zitnik, Percy Liang, Vijay S. Pande, Jure Leskovec:
Strategies for Pre-training Graph Neural Networks. ICLR 2020 - [c25]Hongyu Ren, Weihua Hu, Jure Leskovec:
Query2box: Reasoning over Knowledge Graphs in Vector Space Using Box Embeddings. ICLR 2020 - [c24]Weihua Hu, Matthias Fey, Marinka Zitnik, Yuxiao Dong, Hongyu Ren, Bowen Liu, Michele Catasta, Jure Leskovec:
Open Graph Benchmark: Datasets for Machine Learning on Graphs. NeurIPS 2020 - [i11]Hongyu Ren, Weihua Hu, Jure Leskovec:
Query2box: Reasoning over Knowledge Graphs in Vector Space using Box Embeddings. CoRR abs/2002.05969 (2020) - [i10]Weihua Hu, Matthias Fey, Marinka Zitnik, Yuxiao Dong, Hongyu Ren, Bowen Liu, Michele Catasta, Jure Leskovec:
Open Graph Benchmark: Datasets for Machine Learning on Graphs. CoRR abs/2005.00687 (2020) - [i9]C. Lawrence Zitnick, Lowik Chanussot, Abhishek Das, Siddharth Goyal, Javier Heras-Domingo, Caleb Ho, Weihua Hu, Thibaut Lavril, Aini Palizhati, Morgane Riviere, Muhammed Shuaibi, Anuroop Sriram, Kevin Tran, Brandon M. Wood, Junwoong Yoon, Devi Parikh, Zachary W. Ulissi:
An Introduction to Electrocatalyst Design using Machine Learning for Renewable Energy Storage. CoRR abs/2010.09435 (2020) - [i8]Lowik Chanussot, Abhishek Das, Siddharth Goyal, Thibaut Lavril, Muhammed Shuaibi, Morgane Riviere, Kevin Tran, Javier Heras-Domingo, Caleb Ho, Weihua Hu, Aini Palizhati, Anuroop Sriram, Brandon M. Wood, Junwoong Yoon, Devi Parikh, C. Lawrence Zitnick, Zachary W. Ulissi:
The Open Catalyst 2020 (OC20) Dataset and Community Challenges. CoRR abs/2010.09990 (2020) - [i7]Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Sara Beery, Jure Leskovec, Anshul Kundaje, Emma Pierson, Sergey Levine, Chelsea Finn, Percy Liang:
WILDS: A Benchmark of in-the-Wild Distribution Shifts. CoRR abs/2012.07421 (2020)
2010 – 2019
- 2019
- [c23]Keyulu Xu, Weihua Hu, Jure Leskovec, Stefanie Jegelka:
How Powerful are Graph Neural Networks? ICLR 2019 - [p1]Weihua Hu, Takeru Miyato, Seiya Tokui, Eiichi Matsumoto, Masashi Sugiyama:
Unsupervised Discrete Representation Learning. Explainable AI 2019: 97-119 - [i6]Weihua Hu, Bowen Liu, Joseph Gomes, Marinka Zitnik, Percy Liang, Vijay S. Pande, Jure Leskovec:
Pre-training Graph Neural Networks. CoRR abs/1905.12265 (2019) - 2018
- [c22]Weihua Hu, Gang Niu, Issei Sato, Masashi Sugiyama:
Does Distributionally Robust Supervised Learning Give Robust Classifiers? ICML 2018: 2034-2042 - [c21]Bo Han, Quanming Yao, Xingrui Yu, Gang Niu, Miao Xu, Weihua Hu, Ivor W. Tsang, Masashi Sugiyama:
Co-teaching: Robust training of deep neural networks with extremely noisy labels. NeurIPS 2018: 8536-8546 - [i5]Bo Han, Quanming Yao, Xingrui Yu, Gang Niu, Miao Xu, Weihua Hu, Ivor W. Tsang, Masashi Sugiyama:
Co-sampling: Training Robust Networks for Extremely Noisy Supervision. CoRR abs/1804.06872 (2018) - [i4]Keyulu Xu, Weihua Hu, Jure Leskovec, Stefanie Jegelka:
How Powerful are Graph Neural Networks? CoRR abs/1810.00826 (2018) - 2017
- [j7]Weihua Hu, Hirosuke Yamamoto, Junya Honda:
Worst-case Redundancy of Optimal Binary AIFV Codes and Their Extended Codes. IEEE Trans. Inf. Theory 63(8): 5074-5086 (2017) - [c20]Weihua Hu, Takeru Miyato, Seiya Tokui, Eiichi Matsumoto, Masashi Sugiyama:
Learning Discrete Representations via Information Maximizing Self-Augmented Training. ICML 2017: 1558-1567 - [c19]Weihua Hu, Haizhen He:
The construction of Chinese-English Parallel translation corpus. ICSAI 2017: 690-695 - [c18]Takashi Ishida, Gang Niu, Weihua Hu, Masashi Sugiyama:
Learning from Complementary Labels. NIPS 2017: 5639-5649 - [i3]Weihua Hu, Takeru Miyato, Seiya Tokui, Eiichi Matsumoto, Masashi Sugiyama:
Learning Discrete Representations via Information Maximizing Self Augmented Training. CoRR abs/1702.08720 (2017) - 2016
- [j6]Elsa Sá Caetano, Álvaro Cunha, Carlos Moutinho, Weihua Hu:
Continuous Dynamic Monitoring of Lively Footbridges. Int. J. Online Eng. 12(4): 49-51 (2016) - [c17]Weihua Hu, Jun'ichi Tsujii:
A Latent Concept Topic Model for Robust Topic Inference Using Word Embeddings. ACL (2) 2016 - [c16]Yuangang Yao, Lei Zhang, Jin Yi, Yong Peng, Weihua Hu, Lei Shi:
A Framework for Big Data Security Analysis and the Semantic Technology. ICITCS 2016: 1-4 - [c15]Weihua Hu, Hirosuke Yamamoto, Junya Honda:
Tight upper bounds on the redundancy of optimal binary AIFV codes. ISIT 2016: 6-10 - [i2]Weihua Hu, Hirosuke Yamamoto, Junya Honda:
Worst-case Redundancy of Optimal Binary AIFV Codes and their Extended Codes. CoRR abs/1607.07247 (2016) - [i1]Weihua Hu, Issei Sato, Masashi Sugiyama:
Robust supervised learning under uncertainty in dataset shift. CoRR abs/1611.02041 (2016) - 2015
- [j5]Bin Liu, Xinjian Luo, Rui Huang, Chao Wan, Bingbing Zhang, Weihua Hu, Zongge Yue:
Corrigendum to: "Virtual plate pre-bending for the long bone fracture based on axis pre-alignment" [Computerized Medical Imaging and Graphics. 38 (4) (2014) 233-244]. Comput. Medical Imaging Graph. 43: 165 (2015) - [c14]Elsa Sá Caetano, Álvaro Cunha, Carlos Moutinho, Weihua Hu:
Dynamic monitoring of civil engineering structures. exp.at 2015: 79-85 - [c13]Elsa Sá Caetano, Álvaro Cunha, Carlos Moutinho, Weihua Hu:
Dynamic monitoring of lively footbridges. exp.at 2015: 135-136 - [c12]Pengcheng Tang, Fei Li, Wei Zhou, Weihua Hu, Li Yang:
Efficient Auto-Scaling Approach in the Telco Cloud Using Self-Learning Algorithm. GLOBECOM 2015: 1-6 - 2014
- [j4]Bin Liu, Xinjian Luo, Rui Huang, Chao Wan, Bingbing Zhang, Weihua Hu, Zongge Yue:
Virtual plate pre-bending for the long bone fracture based on axis pre-alignment. Comput. Medical Imaging Graph. 38(4): 233-244 (2014) - 2013
- [j3]Kostas Pentikousis, Yan Wang, Weihua Hu:
Mobileflow: Toward software-defined mobile networks. IEEE Commun. Mag. 51(7): 44-53 (2013) - 2010
- [c11]Xiaoliang Xu, Weihua Hu:
Research on J2EE Teaching Based on Mainstream Open Source Frameworks. CIT 2010: 2014-2017
2000 – 2009
- 2009
- [j2]Qing Wu, Weihua Hu, Wen Ding:
A Semantic and Adaptive Middleware Architecture for Pervasive Computing Systems. J. Softw. 4(10): 1061-1068 (2009) - [c10]Jianping Han, Rong Yang, Weihua Hu:
Multi-level and Modulized Experimental Teaching Architecture for Computer Engineering. ScalCom-EmbeddedCom 2009: 547-549 - 2008
- [c9]Qiuhua Zheng, Weihua Hu, Yuntao Qian, Min Yao, Xianglin Wang, Jing Chen:
A Novel Approach for Network Event Correlation Based on Set Covering. FSKD (3) 2008: 122-126 - [c8]Wen Ding, Qing Wu, Weihua Hu, Zhiling Hu, Hongbiao Xie:
A Linux-based Development and Application of Automatic Test System. ICYCS 2008: 2481-2484 - [c7]Qing Wu, Wen Ding, Weihua Hu, Bishui Zhou, Tianzhou Chen:
Computer Ability Assisted Assessment System for Large-Scale Heterogeneous Distributed Environments. ICYCS 2008: 2552-2555 - [c6]Jianping Han, Weihua Hu, Xiaoqing Feng:
Exploration and Practice on Teaching Java as Introductory Language for Non-CSE Major Students. ICYCS 2008: 2696-2700 - 2007
- [c5]Tianzhou Chen, Weihua Hu, Qingsong Shi, Hui Yan:
Embedded education for Computer Rank Examination. ICPADS 2007: 1-4 - 2006
- [c4]Weihua Hu, Chuying Ke, Guorong Wang:
Research of Virtual Campus Environment Study Using VRML. Edutainment 2006: 581-584 - 2005
- [j1]Zhigeng Pan, Jiejie Zhu, Weihua Hu, Hung Pak Lun, Xin Zhou:
Interactive learning of CG in networked virtual environments. Comput. Graph. 29(2): 273-281 (2005) - [c3]Zhigeng Pan, Jiejie Zhu, Mingmin Zhang, Weihua Hu:
Collaborative Virtual Learning Environment Using Synthetic Characters. ICWL 2005: 364-374 - 2003
- [c2]Weihua Hu, Jiejie Zhu, Zhigeng Pan, Yanfeng Li, Cunhui Ju:
Learning by doing: A Case for Constructivist 3D Virtual Learning Environment. Eurographics (Education Papers) 2003 - [c1]Weihua Hu, Jiejie Zhu, Zhigeng Pan:
Exploring an Agent-Driven 3D Learning Environment for Computer Graphics Education. IVA 2003: 355
Coauthor Index
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