Hao Wang

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Dit-Yan YeungChair Professor, Department of CSE, HKUST, Hong KongE-mail confirmado em cse.ust.hk
Xingjian ShiBoson AIE-mail confirmado em connect.ust.hk
Zhourong ChenGoogle ResearchE-mail confirmado em google.com
Wang Chun WOOHong Kong ObservatoryE-mail confirmado em hko.gov.hk
Dina KatabiThuan and Nicole Pham Professor, MITE-mail confirmado em ai.mit.edu
Hao HeMIT, CSAILE-mail confirmado em mit.edu
Carl VondrickAssociate Professor, Columbia UniversityE-mail confirmado em columbia.edu
Junfeng YangAssociate Professor of Computer Science, Columbia UniversityE-mail confirmado em cs.columbia.edu
Wu-Jun LiNanjing UniversityE-mail confirmado em nju.edu.cn
Eric XingPresident at Mohamed bin Zayed University of AI, Professor of Computer Science, Carnegie Mellon UE-mail confirmado em cs.cmu.edu
Shichao YueMITE-mail confirmado em mit.edu
Yonglong TianResearch Scientist, OpenAIE-mail confirmado em mit.edu
Guang-He LeeMITE-mail confirmado em mit.edu
Yinbo ChenPhD student at UC San DiegoE-mail confirmado em ucsd.edu
Zachary C. LiptonRaj Reddy Associate Professor of Machine Learning @ Carnegie Mellon University; CTO + CSO @ AbridgeE-mail confirmado em cmu.edu
Shantanu GuptaCarnegie Mellon UniversityE-mail confirmado em cs.cmu.edu
Hao ZhangUC San DiegoE-mail confirmado em ucsd.edu
Tommi JaakkolaMITE-mail confirmado em csail.mit.edu
Aravinthan SamuelProfessor of Physics, Harvard UniversityE-mail confirmado em g.harvard.edu
Yaron MeirovitchResearch associate at HarvardE-mail confirmado em fas.harvard.edu

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Hao Wang

Assistant Professor of Computer Science, Rutgers University

E-mail confirmado em mit.edu - Página inicial

Statistical Machine Learning Deep Learning Bayesian Deep Learning ML4Health Recommender Systems / Data Mining


Título Ordenar por citações Ordenar por ano Ordenar por título	Citado por Citado por	Ano
Convolutional LSTM network: A machine learning approach for precipitation nowcasting X Shi, Z Chen, H Wang, DY Yeung, WK Wong, W Woo Advances in neural information processing systems 28, 2015	10992	2015
Collaborative deep learning for recommender systems H Wang, N Wang, DY Yeung Proceedings of the 21th ACM SIGKDD International Conference on Knowledge …, 2015	2030	2015
Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model X Shi, H Wang, Z Gao, L Lausen, DY Yeung, W WOO, W Wong Advances in Neural Information Processing Systems, 5620-5630, 2017	1071	2017
Rethinking knowledge graph propagation for zero-shot learning M Kampffmeyer, Y Chen, X Liang, H Wang, Y Zhang, EP Xing Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019	392	2019
Delving into Deep Imbalanced Regression Y Yang, K Zha, YC Chen, H Wang, D Katabi International Conference on Machine Learning (ICML), 2021	383	2021
Towards Bayesian Deep Learning: A Framework and Some Existing Methods H Wang, DY Yeung IEEE Transactions on Knowledge and Data Engineering 28 (12), 3395-3408, 2016, 2016	375	2016
A Survey on Bayesian Deep Learning H Wang, DY Yeung ACM Computing Surveys (CSUR) 53 (5), 1-37, 2020	284	2020
Artificial intelligence-enabled detection and assessment of Parkinson’s disease using nocturnal breathing signals Y Yang, Y Yuan, G Zhang, H Wang, YC Chen, Y Liu, CG Tarolli, ... Nature Medicine 28 (10), 2207-2215, 2022	224	2022
Collaborative Topic Regression with Social Regularization for Tag Recommendation H Wang, B Chen, WJ Li International Joint Conference on Artificial Intelligence (IJCAI), 2719-2725, 2013	209	2013
Extracting Multi-Person Respiration from Entangled RF Signals S Yue, H He, H Wang, H Rahul, D Katabi Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2018	206	2018
Deep Learning and the Weather Forecasting Problem: Precipitation Nowcasting Z Gao, X Shi, H Wang, DY Yeung, W Woo, WK Wong Book Chapter of Deep Learning for the Earth Sciences: A Comprehensive …, 2021	185*	2021
Earthformer: Exploring Space-Time Transformers for Earth System Forecasting Z Gao, X Shi, H Wang, Y Zhu, Y Wang, M Li, DY Yeung Advances in Neural Information Processing Systems (NeurIPS), 2022	178	2022
Relational Stacked Denoising Autoencoder for Tag Recommendation H Wang, X Shi, DY Yeung AAAI Conference on Artificial Intelligence (AAAI), 3052-3058, 2015	160	2015
Continuously Indexed Domain Adaptation H Wang, H He, D Katabi International Conference on Machine Learning (ICML), 2020	139	2020
BodyCompass: Monitoring Sleep Posture with Wireless Signals S Yue, Y Yang, H Wang, H Rahul, D Katabi Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2020	131	2020
Collaborative recurrent autoencoder: Recommend while learning to fill in the blanks H Wang, X Shi, DY Yeung Advances in Neural Information Processing Systems 29, 2016	130	2016
Language models as recommender systems: Evaluations and limitations Y Zhang, H Ding, Z Shui, Y Ma, J Zou, A Deoras, H Wang NeurIPS 2021 Workshop, 2021	98*	2021
Domain Adaptation for Time Series Forecasting via Attention Sharing X Jin, Y Park, DC Maddix, H Wang, Y Wang International Conference on Machine Learning (ICML), 2022	95	2022
Zero-Shot Recommender Systems H Ding, Y Ma, A Deoras, Y Wang, H Wang ICLR 2022 Workshop on Deep Generative Models for Highly Structured Data, 2021	95	2021
Natural-parameter networks: A class of probabilistic neural networks H Wang, X Shi, DY Yeung Advances in neural information processing systems 29, 2016	95	2016

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