Hao Wang

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	Total	Desde 2018
Citas	11743	11061
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Índice i10	39	39

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Dit-Yan YeungChair Professor, Department of CSE, HKUST, Hong KongDirección de correo verificada de cse.ust.hk
Xingjian ShiBoson AIDirección de correo verificada de connect.ust.hk
Zhourong ChenGoogle ResearchDirección de correo verificada de google.com
Wang Chun WOOHong Kong ObservatoryDirección de correo verificada de hko.gov.hk
Dina KatabiProfessor of EECS, MITDirección de correo verificada de ai.mit.edu
Hao HeMIT, CSAILDirección de correo verificada de mit.edu
Naiyan WangTuSimpleDirección de correo verificada de tusimple.com
Xiaodan LiangAssociate Professor, Sun Yat-sen University, CMU, NUSDirección de correo verificada de mail2.sysu.edu.cn
Wu-Jun LiNanjing UniversityDirección de correo verificada de nju.edu.cn
Eric XingPresident at Mohamed bin Zayed University of AI, Professor of Computer Science, Carnegie Mellon UDirección de correo verificada de cs.cmu.edu
Shichao YueMITDirección de correo verificada de mit.edu
Yonglong TianGoogle Research; MITDirección de correo verificada de mit.edu
Michael Christian KampffmeyerAssociate Professor in Machine Learning, UiT the Arctic University of Norway, TromsøDirección de correo verificada de post.uit.no
Yinbo ChenPhD student at UC San DiegoDirección de correo verificada de ucsd.edu
Carl VondrickAssociate Professor, Columbia UniversityDirección de correo verificada de columbia.edu
Junfeng YangAssociate Professor of Computer Science, Columbia UniversityDirección de correo verificada de cs.columbia.edu
Guang-He LeeMITDirección de correo verificada de mit.edu
Binyi ChenUC Santa BarbaraDirección de correo verificada de cs.ucsb.edu
Hao ZhangUC BerkeleyDirección de correo verificada de cs.berkeley.edu
Zachary C. LiptonAssistant Professor at Carnegie Mellon University; Chief Scientific Officer at AbridgeDirección de correo verificada de cmu.edu

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Hao Wang

Assistant Professor of Computer Science, Rutgers University

Dirección de correo verificada de mit.edu - Página principal

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


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
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	7157	2015
Collaborative deep learning for recommender systems H Wang, N Wang, DY Yeung Proceedings of the 21th ACM SIGKDD International Conference on Knowledge …, 2015	1722	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	620	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	296	2019
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	278	2016
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	167	2013
Relational Stacked Denoising Autoencoder for Tag Recommendation. H Wang, X Shi, DY Yeung AAAI Conference on Artificial Intelligence (AAAI), 3052-3058, 2015	154	2015
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	123	2018
A Survey on Bayesian Deep Learning H Wang, DY Yeung ACM Computing Surveys (CSUR) 53 (5), 1-37, 2020	115	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	113	2016
Delving into Deep Imbalanced Regression Y Yang, K Zha, YC Chen, H Wang, D Katabi International Conference on Machine Learning (ICML), 2021	108	2021
Continuously Indexed Domain Adaptation H Wang, H He, D Katabi International Conference on Machine Learning (ICML), 2020	75	2020
Relational Deep Learning: A Deep Latent Variable Model for Link Prediction. H Wang, X Shi, DY Yeung AAAI Conference on Artificial Intelligence (AAAI), 2688-2694, 2017	71	2017
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	68*	2021
Natural-parameter networks: A class of probabilistic neural networks H Wang, X Shi, DY Yeung Advances in neural information processing systems 29, 2016	66	2016
Relational collaborative topic regression for recommender systems H Wang, WJ Li IEEE Transactions on Knowledge and Data Engineering 27 (5), 1343-1355, 2015	65	2015
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	56	2020
ProbGAN: Towards Probabilistic GAN with Theoretical Guarantees H He, H Wang, GH Lee, Y Tian International Conference on Learning Representations (ICLR), 2019	38*	2019
Paint transformer: Feed forward neural painting with stroke prediction S Liu, T Lin, D He, F Li, R Deng, X Li, E Ding, H Wang Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021	36	2021
ZM-Net: Real-time Zero-shot Image Manipulation Network H Wang, X Liang, H Zhang, DY Yeung, EP Xing arXiv preprint arXiv:1703.07255, 2017	36	2017

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