Chen Zhu

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Tom GoldsteinVolpi-Cupal Professor of Computer Science, University of MarylandDirección de correo verificada de cs.umd.edu
Yu ChengVisiting Professor at Rice UniversityDirección de correo verificada de rice.edu
Zhe GanResearch Scientist, AppleDirección de correo verificada de apple.com
W. Ronny HuangGoogle ResearchDirección de correo verificada de google.com
Kezhi KongUniversity of Maryland, College ParkDirección de correo verificada de cs.umd.edu
Hengduo LiMeta AIDirección de correo verificada de meta.com
Yi Ma (马毅)Professor of EECS, UC Berkeley; Director of IDS & Head of CS, University of Hong KongDirección de correo verificada de eecs.berkeley.edu
Micah GoldblumNew York UniversityDirección de correo verificada de nyu.edu
Furong HuangAssistant Professor of Computer Science, University of MarylandDirección de correo verificada de umd.edu
Zheng XuGoogle ResearchDirección de correo verificada de google.com
Ali ShafahiAppleDirección de correo verificada de umd.edu
Chaowei XiaoUniversity of Wisconsin - MadisonDirección de correo verificada de umich.edu
Wei PingPrincipal Research Scientist, NVIDIADirección de correo verificada de nvidia.com
Bryan CatanzaroNVIDIADirección de correo verificada de acm.org
Mohammad ShoeybiDirector of Applied Research at NVIDIADirección de correo verificada de nvidia.com
Bin Dai清华大学Dirección de correo verificada de mails.tsinghua.edu.cn
Ankit Singh RawatResearch Scientist, GoogleDirección de correo verificada de google.com
Manzil ZaheerGoogle ResearchDirección de correo verificada de cmu.edu
Srinadh BhojanapalliResearch Scientist, Google ResearchDirección de correo verificada de google.com
Kewei TuSchool of Information Science and Technology, ShanghaiTech University, ChinaDirección de correo verificada de shanghaitech.edu.cn

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Chen Zhu

Nvidia

Dirección de correo verificada de nvidia.com - Página principal

Machine Learning Natural Language Processing Computer Vision


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Large-Scale Adversarial Training for Vision-and-Language Representation Learning Z Gan, YC Chen, L Li, C Zhu, Y Cheng, J Liu NeurIPS 2020 & arXiv:2006.06195, 2020	408	2020
Freelb: Enhanced adversarial training for natural language understanding C Zhu, Y Cheng, Z Gan, S Sun, T Goldstein, J Liu ICLR 2020 & arXiv:1909.11764, 2020	396	2020
Transferable Clean-Label Poisoning Attacks on Deep Neural Nets C Zhu, WR Huang, A Shafahi, H Li, G Taylor, C Studer, T Goldstein ICML 2019 & arXiv: 1905.05897, 2019	271	2019
Compressing neural networks using the variational information bottleneck B Dai, C Zhu, B Guo, D Wipf ICML 2018 & arXiv: 1802.10399, 2018	172	2018
A field guide to federated optimization J Wang, Z Charles, Z Xu, G Joshi, HB McMahan, M Al-Shedivat, G Andrew, ... arXiv preprint arXiv:2107.06917, 2021	154	2021
The Intrinsic Dimension of Images and Its Impact on Learning P Pope, C Zhu, A Abdelkader, M Goldblum, T Goldstein ICLR 2021 & arXiv:2104.08894, 2021	148	2021
Robust optimization as data augmentation for large-scale graphs K Kong, G Li, M Ding, Z Wu, C Zhu, B Ghanem, G Taylor, T Goldstein Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022	144*	2022
Certified defenses for adversarial patches PY Chiang, R Ni, A Abdelkader, C Zhu, C Studor, T Goldstein ICLR 2020 & arXiv:2003.06693, 2020	141	2020
Adversarially robust transfer learning A Shafahi, P Saadatpanah, C Zhu, A Ghiasi, C Studer, D Jacobs, ... ICLR 2020 & arXiv:1905.08232, 2019	124	2019
Structured attentions for visual question answering C Zhu, Y Zhao, S Huang, K Tu, Y Ma ICCV 2017 & arXiv: 1708.02071, 2017	113	2017
Deep k-NN Defense Against Clean-Label Data Poisoning Attacks N Peri, N Gupta, WR Huang, L Fowl, C Zhu, S Feizi, T Goldstein, ... Computer Vision–ECCV 2020 Workshops: Glasgow, UK, August 23–28, 2020 …, 2020	103	2020
Learning from Noisy Anchors for One-stage Object Detection H Li, Z Wu, C Zhu, C Xiong, R Socher, LS Davis CVPR 2020 & arXiv:1912.05086, 2019	90	2019
Long-short transformer: Efficient transformers for language and vision C Zhu, W Ping, C Xiao, M Shoeybi, T Goldstein, A Anandkumar, ... NeurIPS 2021 & arXiv:2107.02192, 2021	83	2021
Learning visual knowledge memory networks for visual question answering Z Su, C Zhu, Y Dong, D Cai, Y Chen, J Li CVPR 2018 & arXiv: 1806.04860, 2018	76	2018
Modifying memories in transformer models C Zhu, AS Rawat, M Zaheer, S Bhojanapalli, D Li, F Yu, S Kumar arXiv preprint arXiv:2012.00363, 2020	54	2020
Fine-grained video categorization with redundancy reduction attention C Zhu, X Tan, F Zhou, X Liu, K Yue, E Ding, Y Ma Proceedings of the European Conference on Computer Vision (ECCV), 136-152, 2018	53	2018
GradInit: Learning to initialize neural networks for stable and efficient training C Zhu, R Ni, Z Xu, K Kong, WR Huang, T Goldstein NeurIPS 2021 & arXiv:2102.08098, 2021	44	2021
Are Adversarial Examples Created Equal? A Learnable Weighted Minimax Risk for Robustness under Non-uniform Attacks H Zeng, C Zhu, T Goldstein, F Huang AAAI 2021 & arXiv:2010.12989, 2020	19	2020
Robust plane-based calibration of multiple non-overlapping cameras C Zhu, Z Zhou, Z Xing, Y Dong, Y Ma, J Yu 2016 Fourth International Conference on 3D Vision (3DV), 658-666, 2016	19	2016
Diurnal or Nocturnal? Federated Learning of Multi-branch Networks from Periodically Shifting Distributions C Zhu, Z Xu, M Chen, J Konečný, A Hard, T Goldstein ICLR 2022 & NeurIPS 2021 Workshop on Distribution Shifts, 2022	16	2022

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