Shanghang Zhang

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Kurt KeutzerProfessor of the Graduate School, EECS, University of California, BerkeleyVerified email at berkeley.edu
Jose M. F. MouraPhilip L. and Marsha Dowd University Professor, Carnegie Mellon UniversityVerified email at ece.cmu.edu
Jianxin LiSchool of Computer Science & Engineering, Beihang UniversityVerified email at act.buaa.edu.cn
Haoyi ZhouAssistant Professor, Beihang UniversityVerified email at buaa.edu.cn
Guanhang WuGoogle Inc / CMU RoboticsVerified email at google.com
Han ZhaoAssistant Professor of Computer Science, University of Illinois at Urbana-ChampaignVerified email at illinois.edu
Xiangyu YueThe Chinese University of Hong KongVerified email at ie.cuhk.edu.hk
Geoff GordonProfessor of Machine Learning, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Trevor DarrellProfessor of Computer Science, U.C. BerkeleyVerified email at eecs.berkeley.edu
Sicheng ZhaoTsinghua UniversityVerified email at tsinghua.edu.cn
Alberto Sangiovanni VincentelliProfessor of EECS, University of California, BerkeleyVerified email at eecs.berkeley.edu
Jian DuTikTok, US (was CMU (was McGill (was HKU)))Verified email at andrew.cmu.edu
Xuezhe MaInformation Sciences Institute, University of Southern CaliforniaVerified email at usc.edu
Soummya KarElectrical and Computer Engineering, Carnegie Mellon UniversityVerified email at andrew.cmu.edu
Swarun KumarAssociate Professor, CMUVerified email at cmu.edu
Zhe L. LinSenior Principal Scientist, Adobe ResearchVerified email at adobe.com
Radomir MechAdobe SystemsVerified email at adobe.com
Xiaohui ShenByteDance ResearchVerified email at bytedance.com
Satwik KotturResearch Scientist, Facebook AIVerified email at fb.com

Shanghang Zhang

EECS, UC Berkeley

Verified email at eecs.berkeley.edu - Homepage

Machine Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Informer: Beyond efficient transformer for long sequence time-series forecasting H Zhou, S Zhang, J Peng, S Zhang, J Li, H Xiong, W Zhang Proceedings of the AAAI conference on artificial intelligence 35 (12), 11106 …, 2021	1755	2021
COVID-CT-Dataset: a CT scan dataset about COVID-19 X Yang, X He, J Zhao, Y Zhang, S Zhang, P Xie arXiv preprint arXiv:2003.13865, 2020	930*	2020
Adversarial multiple source domain adaptation H Zhao, S Zhang, G Wu, JMF Moura, JP Costeira, GJ Gordon Advances in neural information processing systems 31, 8559-8570, 2018	498	2018
Sample-Efficient Deep Learning for COVID-19 Diagnosis Based on CT Scans X He, X Yang, S Zhang*, J Zhao, Y Zhang, E Xing, P Xie medRxiv, 2020	408	2020
Topology adaptive graph convolutional networks J Du, S Zhang, G Wu, JMF Moura, S Kar arXiv:1710.10370, 2017	261	2017
Universal Self-Training for Unsupervised Domain Adaptation K Mei, C Zhu, J Zou, S Zhang European Conference on Computer Vision (ECCV), 2020	239*	2020
FCN-rLSTM: Deep Spatio-Temporal Neural Networks for Vehicle Counting in City Cameras S Zhang, G Wu, JP Costeira, JMF Moura International Conference on Computer Vision (ICCV), 2017	236	2017
A review of single-source deep unsupervised visual domain adaptation S Zhao, X Yue, S Zhang, B Li, H Zhao, B Wu, R Krishna, JE Gonzalez, ... IEEE Transactions on Neural Networks and Learning Systems, 2020	190	2020
Multi-source Distilling Domain Adaptation S Zhao, G Wang, S Zhang*, Y Gu, Y Li, Z Song, P Xu, R Hu, H Chai, ... Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020	173	2020
Deep Reinforcement Learning H Dong, Z Ding, S Zhang Springer Singapore, 2020	172	2020
Understanding Traffic Density from Large-Scale Web Camera Data S Zhang, G Wu, JP Costeira, JMF Moura IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017	164	2017
Prototypical Cross-domain Self-supervised Learning for Few-shot Unsupervised Domain Adaptation X Yue, Z Zheng, S Zhang, Y Gao, T Darrell, K Keutzer, AS Vincentelli CVPR 2021, 2021	119	2021
A Deep Learning Approach to IoT Authentication R Das, A Gadre, S Zhang, S Kumar, J Moura IEEE ICC 2018 Communication and Information Systems Security Symposium, 2018	118	2018
Differentiable spike: Rethinking gradient-descent for training spiking neural networks Y Li, Y Guo, S Zhang, S Deng, Y Hai, S Gu Advances in Neural Information Processing Systems 34, 23426-23439, 2021	117	2021
Temporal efficient training of spiking neural network via gradient re-weighting S Deng, Y Li, S Zhang, S Gu arXiv preprint arXiv:2202.11946, 2022	115	2022
Self-supervised pretraining improves self-supervised pretraining CJ Reed, X Yue, A Nrusimha, S Ebrahimi, V Vijaykumar, R Mao, B Li, ... Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2022	79	2022
Learning Invariant Representations and Risks for Semi-supervised Domain Adaptation B Li#, Y Wang#, S Zhang#, D Li, T Darrell, K Keutzer, H Zhao CVPR 2021, 2021	78	2021
Dual adversarial semantics-consistent network for generalized zero-shot learning J Ni, S Zhang, H Xie Advances in neural information processing systems 32, 2019	74	2019
Unsupervised domain adaptive 3d detection with multi-level consistency Z Luo, Z Cai, C Zhou, G Zhang, H Zhao, S Yi, S Lu, H Li, S Zhang, Z Liu Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021	63	2021
Delving deep into the generalization of vision transformers under distribution shifts C Zhang#, M Zhang#, S Zhang#, D Jin, Q Zhou, Z Cai, H Zhao, S Yi, X Liu, ... Conference on Computer Vision and Pattern Recognition (CVPR), 2022	55	2022

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