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Author

Hao Wang

Observed names: Wang Hao, Wang, Hao
Institutions: Rutgers, The State University of New Jersey, IBM (United States), University of Illinois Urbana-Champaign, Duke University, Peking University, Mohamed bin Zayed University of Artificial Intelligence, Imperial College London, Massachusetts Institute of Technology
Observed institutions: Rutgers, The State University of New Jersey, Centre National de la Recherche Scientifique, IBM (United States), University of Illinois Urbana-Champaign, Duke University, Hong Kong University of Science and Technology, Peking University, Université Paris Sciences et Lettres, Laboratoire Kastler Brossel, École Normale Supérieure - PSL, Sorbonne Université, Nokia (China), Mohamed bin Zayed University of Artificial Intelligence, MIT Computer Science and Artificial Intelligence Laboratory, Imperial College London, Massachusetts Institute of Technology, Nanjing University, Tsinghua University
ORCID: 0000-0002-7308-938X
Observed ORCID: 0000-0002-7308-938X
OpenAlex ID: A5101533496
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
2015 · Shi, Xingjian, Chen, Zhourong, et al. · arXiv (Cornell University) · 8,045
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Collaborative Deep Learning for Recommender Systems
2015 · Hao Wang, Naiyan Wang, et al. · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · 1,676
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Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model
2017 · Shi, Xingjian, Gao, Zhihan, et al. · arXiv (Cornell University) · 876
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Rethinking Knowledge Graph Propagation for Zero-Shot Learning
2019 · Michael Kampffmeyer, Yinbo Chen, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 376
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Artificial intelligence-enabled detection and assessment of Parkinson’s disease using nocturnal breathing signals
2022 · Yuzhe Yang, Yuan Yuan, et al. · Nature Medicine · 314
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A Survey on Bayesian Deep Learning
2020 · Hao Wang, Dit-Yan Yeung · ACM Computing Surveys · 287
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Towards Bayesian Deep Learning: A Framework and Some Existing Methods
2016 · Hao Wang, Dit-Yan Yeung · IEEE Transactions on Knowledge and Data Engineering · 285
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Delving into Deep Imbalanced Regression
2021 · Yang, Yuzhe, Zha, Kaiwen, et al. · arXiv (Cornell University) · 259
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BodyCompass
2020 · Shichao Yue, Yuzhe Yang, et al. · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · 122
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Assessment of medication self-administration using artificial intelligence
2021 · Mingmin Zhao, Kreshnik Hoti, et al. · Nature Medicine · 70
Earthformer: Exploring Space-Time Transformers for Earth System Forecasting
2022 · Zhihan Gao, Xingjian Shi, et al. · neural information processing systems · 69
Relational Collaborative Topic Regression for Recommender Systems
2014 · Hao Wang, Wu-Jun Li · IEEE Transactions on Knowledge and Data Engineering · 69
OrphicX: A Causality-Inspired Latent Variable Model for Interpreting Graph Neural Networks
2022 · Wanyu Lin, Hao Lan, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 65
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Relational Deep Learning: A Deep Latent Variable Model for Link Prediction
2017 · Hao Wang, Xingjian Shi, et al. · Proceedings of the AAAI Conference on Artificial Intelligence · 64
Bayesian Invariant Risk Minimization
2022 · Yong Lin, Hanze Dong, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 62
On Multi-Domain Long-Tailed Recognition, Imbalanced Domain Generalization and Beyond
2022 · Yuzhe Yang, Hao Wang, et al. · Lecture notes in computer science · 61
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Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting
2023 · Marcel Kollovieh, Abdul Fatir Ansari, et al. · neural information processing systems · 59
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Roadmap on Neuromorphic Photonics
2025 · Brunner, Daniel, Shastri, Bhavin J., et al. · arXiv (Cornell University) · 54
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Natural-Parameter Networks: A Class of Probabilistic Neural Networks
2016 · Wang, Hao, Shi, Xingjian, et al. · arXiv (Cornell University) · 53
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Domain Adaptation for Time Series Forecasting via Attention Sharing
2021 · Jin, Xiaoyong, Park, Youngsuk, et al. · arXiv (Cornell University) · 44
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BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models
2024 · Yibin Wang, Haizhou Shi, et al. · neural information processing systems · 32
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Social ODE: Multi-agent Trajectory Forecasting with Neural Ordinary Differential Equations
2022 · Song Wen, Hao Wang, et al. · Lecture notes in computer science · 31
A Unified Approach to Domain Incremental Learning with Memory: Theory and Algorithm
2023 · Haizhou Shi, Hao Wang · neural information processing systems · 30
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Training-Free Uncertainty Estimation for Dense Regression: Sensitivity as a Surrogate
2022 · Lu Mi, Hao Wang, et al. · Proceedings of the AAAI Conference on Artificial Intelligence · 29
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ZM-Net: Real-time Zero-shot Image Manipulation Network
2017 · Wang, Hao, Liang, Xiaodan, et al. · arXiv (Cornell University) · 29
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Works count: 95
Citation count: 13,630
H-index: 27
I10-index: 47
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