Hao Wang

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Dit-Yan YeungChair Professor, Department of CSE, HKUST, Hong KongEmail yang diverifikasi di cse.ust.hk
Xingjian ShiBoson AIEmail yang diverifikasi di connect.ust.hk
Zhourong ChenGoogle ResearchEmail yang diverifikasi di google.com
Wang Chun WOOHong Kong ObservatoryEmail yang diverifikasi di hko.gov.hk
Dina KatabiThuan and Nicole Pham Professor, MITEmail yang diverifikasi di ai.mit.edu
Hao HeMIT, CSAILEmail yang diverifikasi di mit.edu
Carl VondrickAssociate Professor, Columbia UniversityEmail yang diverifikasi di columbia.edu
Junfeng YangAssociate Professor of Computer Science, Columbia UniversityEmail yang diverifikasi di cs.columbia.edu
Wu-Jun LiNanjing UniversityEmail yang diverifikasi di nju.edu.cn
Eric XingPresident at Mohamed bin Zayed University of AI, Professor of Computer Science, Carnegie Mellon UEmail yang diverifikasi di cs.cmu.edu
Shichao YueMITEmail yang diverifikasi di mit.edu
Yonglong TianResearch Scientist, OpenAIEmail yang diverifikasi di mit.edu
Guang-He LeeMITEmail yang diverifikasi di mit.edu
Yinbo ChenPhD student at UC San DiegoEmail yang diverifikasi di ucsd.edu
Zachary C. LiptonRaj Reddy Associate Professor of Machine Learning @ Carnegie Mellon University; CTO + CSO @ AbridgeEmail yang diverifikasi di cmu.edu
Shantanu GuptaCarnegie Mellon UniversityEmail yang diverifikasi di cs.cmu.edu
Hao ZhangUC San DiegoEmail yang diverifikasi di ucsd.edu
Tommi JaakkolaMITEmail yang diverifikasi di csail.mit.edu
Aravinthan SamuelProfessor of Physics, Harvard UniversityEmail yang diverifikasi di g.harvard.edu
Yaron MeirovitchResearch associate at HarvardEmail yang diverifikasi di fas.harvard.edu

Ikuti

Hao Wang

Assistant Professor of Computer Science, Rutgers University

Email yang diverifikasi di mit.edu - Beranda

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


Judul Urutkan menurut kutipan Urutkan menurut tahun Urutkan menurut judul	Dikutip oleh Dikutip oleh	Tahun
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	11001	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	1073	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	385	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	179	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	140	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
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	96	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
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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