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ORCIDNanyang Ye 0001
Person information
- affiliation: Shanghai Jiao Tong University, China
- affiliation (PhD 2020): University of Cambridge, UK
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Books and Theses
- 2020
[b1]Nanyang Ye:
Visibility metrics and their applications in visually lossless image compression. University of Cambridge, UK, 2020
Journal Articles
- 2024
- [j6]Lin Zhu
, Weihan Yin, Yiyao Yang, Fan Wu, Zhaoyu Zeng, Qinying Gu, Xinbing Wang, Chenghu Zhou, Nanyang Ye:
Vision-Language Alignment Learning Under Affinity and Divergence Principles for Few-Shot Out-of-Distribution Generalization. Int. J. Comput. Vis. 132(9): 3375-3407 (2024) - [j5]Nanyang Ye, Zhaoyu Zeng, Jundong Zhou, Lin Zhu, Yuxiao Duan, Yifei Wu, Junqi Wu, Haoqi Zeng, Qinying Gu, Xinbing Wang, Chenghu Zhou:
OoD-Control: Generalizing Control in Unseen Environments. IEEE Trans. Pattern Anal. Mach. Intell. 46(11): 7421-7433 (2024) - [j4]Chensheng Peng, Zhaoyu Zeng, Jinling Gao, Jundong Zhou, Masayoshi Tomizuka, Xinbing Wang, Chenghu Zhou, Nanyang Ye:
PNAS-MOT: Multi-Modal Object Tracking With Pareto Neural Architecture Search. IEEE Robotics Autom. Lett. 9(5): 4377-4384 (2024) - 2023
- [j3]Nanyang Ye, Qianxiao Li, Xiao-Yun Zhou, Zhanxing Zhu:
An Annealing Mechanism for Adversarial Training Acceleration. IEEE Trans. Neural Networks Learn. Syst. 34(2): 882-893 (2023) - 2022
- [j2]Ningyi Liao, Shufan Wang, Liyao Xiang, Nanyang Ye, Shuo Shao, Pengzhi Chu:
Achieving adversarial robustness via sparsity. Mach. Learn. 111(2): 685-711 (2022) - 2018
- [j1]Krzysztof Wolski, Daniele Giunchi, Nanyang Ye, Piotr Didyk, Karol Myszkowski, Radoslaw Mantiuk, Hans-Peter Seidel, Anthony Steed, Rafal K. Mantiuk:
Dataset and Metrics for Predicting Local Visible Differences. ACM Trans. Graph. 37(5): 172 (2018)
Conference and Workshop Papers
- 2024
- [c24]Fan Wu, Jinling Gao, Lanqing Hong, Xinbing Wang, Chenghu Zhou, Nanyang Ye:
G-NAS: Generalizable Neural Architecture Search for Single Domain Generalization Object Detection. AAAI 2024: 5958-5966 - [c23]Xilong Zhao, Siyuan Bian, Yaoyun Zhang, Yuliang Zhang, Qinying Gu, Xinbing Wang, Chenghu Zhou, Nanyang Ye:
Domain Invariant Learning for Gaussian Processes and Bayesian Exploration. AAAI 2024: 17024-17032 - [c22]Lin Zhu, Yifeng Yang, Qinying Gu, Xinbing Wang, Chenghu Zhou, Nanyang Ye:
CRoFT: Robust Fine-Tuning with Concurrent Optimization for OOD Generalization and Open-Set OOD Detection. ICML 2024 - 2023
- [c21]Nanyang Ye, Lin Zhu, Jia Wang, Zhaoyu Zeng, Jiayao Shao, Chensheng Peng, Bikang Pan, Kaican Li, Jun Zhu:
Certifiable Out-of-Distribution Generalization. AAAI 2023: 10927-10935 - [c20]Lin Zhu, Xinbing Wang, Chenghu Zhou, Nanyang Ye:
Bayesian Cross-Modal Alignment Learning for Few-Shot Out-of-Distribution Generalization. AAAI 2023: 11461-11469 - 2022
- [c19]Linfeng Cao, Aofan Jiang, Wei Li, Huaying Wu, Nanyang Ye:
OoDHDR-Codec: Out-of-Distribution Generalization for HDR Image Compression. AAAI 2022: 158-166 - [c18]Runpeng Yu, Hong Zhu, Kaican Li, Lanqing Hong, Rui Zhang, Nanyang Ye, Shao-Lun Huang, Xiuqiang He:
Regularization Penalty Optimization for Addressing Data Quality Variance in OoD Algorithms. AAAI 2022: 8945-8953 - [c17]Nanyang Ye, Kaican Li, Haoyue Bai, Runpeng Yu, Lanqing Hong, Fengwei Zhou, Zhenguo Li, Jun Zhu:
OoD-Bench: Quantifying and Understanding Two Dimensions of Out-of-Distribution Generalization. CVPR 2022: 7937-7948 - 2021
- [c16]Haoyue Bai, Rui Sun, Lanqing Hong, Fengwei Zhou, Nanyang Ye, Han-Jia Ye, S.-H. Gary Chan, Zhenguo Li:
DecAug: Out-of-Distribution Generalization via Decomposed Feature Representation and Semantic Augmentation. AAAI 2021: 6705-6713 - [c15]Nanyang Ye, Qianxiao Li, Xiao-Yun Zhou, Zhanxing Zhu:
Amata: An Annealing Mechanism for Adversarial Training Acceleration. AAAI 2021: 10691-10699 - [c14]Nanyang Ye, Jingxuan Tang, Huayu Deng, Xiao-Yun Zhou, Qianxiao Li, Zhenguo Li, Guang-Zhong Yang, Zhanxing Zhu:
Adversarial Invariant Learning. CVPR 2021: 12446-12454 - [c13]Nanyang Ye, Jingbiao Mei, Zhicheng Fang, Yuwen Zhang, Ziqing Zhang, Huaying Wu, Xiaoyao Liang:
BayesFT: Bayesian Optimization for Fault Tolerant Neural Network Architecture. DAC 2021: 487-492 - [c12]Karl Chahine, Nanyang Ye, Hyeji Kim:
DeepIC: Coding for Interference Channels via Deep Learning. GLOBECOM 2021: 1-6 - [c11]Aliaksei Mikhailiuk, Nanyang Ye, Rafal K. Mantiuk:
The effect of display brightness and viewing distance: a dataset for visually lossless image compression. HVEI 2021 - [c10]Haoyue Bai, Fengwei Zhou, Lanqing Hong, Nanyang Ye, S.-H. Gary Chan, Zhenguo Li:
NAS-OoD: Neural Architecture Search for Out-of-Distribution Generalization. ICCV 2021: 8300-8309 - [c9]Yu Chen, Yuxuan Wang, Bolin Lai, Zijie Chen, Xu Cao, Nanyang Ye, Zhongyuan Ren, Junbo Zhao, Xiao-Yun Zhou, Peng Qi:
Semi-supervised Vein Segmentation of Ultrasound Images for Autonomous Venipuncture. IROS 2021: 9475-9481 - 2019
- [c8]Nanyang Ye, Krzysztof Wolski, Rafal K. Mantiuk:
Predicting Visible Image Differences Under Varying Display Brightness and Viewing Distance. CVPR 2019: 5434-5442 - [c7]Nanyang Ye, María Pérez-Ortiz, Rafal K. Mantiuk:
Visibility Metric for Visually Lossless Image Compression. PCS 2019: 1-5 - 2018
- [c6]Nanyang Ye, María Pérez-Ortiz, Rafal K. Mantiuk:
Trained Perceptual Transform for Quality Assessment of High Dynamic Range Images and Video. ICIP 2018: 1718-1722 - [c5]Nanyang Ye, Zhanxing Zhu:
Stochastic Fractional Hamiltonian Monte Carlo. IJCAI 2018: 3019-3025 - [c4]Nanyang Ye, Zhanxing Zhu:
Bayesian Adversarial Learning. NeurIPS 2018: 6892-6901 - 2017
- [c3]Nanyang Ye, Zhanxing Zhu, Rafal Mantiuk:
Langevin Dynamics with Continuous Tempering for Training Deep Neural Networks. NIPS 2017: 618-626 - 2016
- [c2]Nanyang Ye, Xiaoming Tao, Linhao Dong, Ning Ge:
Mouse calibration aided real-time gaze estimation based on boost Gaussian Bayesian learning. ICIP 2016: 2797-2801 - 2015
- [c1]Nanyang Ye, Linhao Dong, Xiaoming Tao, Ning Ge:
Efficient Multi-Cell Clustering for Coordinated Multi-Point Transmission with Blossom Tree Algorithm. VTC Fall 2015: 1-4
Informal and Other Publications
- 2024
- [i17]Fan Wu, Jinling Gao, Lanqing Hong, Xinbing Wang, Chenghu Zhou, Nanyang Ye:
G-NAS: Generalizable Neural Architecture Search for Single Domain Generalization Object Detection. CoRR abs/2402.04672 (2024) - [i16]Xinbing Wang, Luoyi Fu, Xiaoying Gan, Ying Wen, Guanjie Zheng, Jiaxin Ding, Liyao Xiang, Nanyang Ye, Meng Jin, Shiyu Liang, Bin Lu, Haiwen Wang, Yi Xu, Cheng Deng, Shao Zhang, Huquan Kang, Xingli Wang, Qi Li, Zhixin Guo, Jiexing Qi, Pan Liu, Yuyang Ren, Lyuwen Wu, Jungang Yang, Jianping Zhou, Chenghu Zhou:
AceMap: Knowledge Discovery through Academic Graph. CoRR abs/2403.02576 (2024) - [i15]Qiao Sun, Liujia Yang, Minghao Ma, Nanyang Ye, Qinying Gu:
Rethinking ASTE: A Minimalist Tagging Scheme Alongside Contrastive Learning. CoRR abs/2403.07342 (2024) - [i14]Chensheng Peng, Zhaoyu Zeng, Jinling Gao, Jundong Zhou, Masayoshi Tomizuka, Xinbing Wang, Chenghu Zhou, Nanyang Ye:
PNAS-MOT: Multi-Modal Object Tracking with Pareto Neural Architecture Search. CoRR abs/2403.15712 (2024) - [i13]Lin Zhu, Yifeng Yang, Qinying Gu, Xinbing Wang, Chenghu Zhou, Nanyang Ye:
CRoFT: Robust Fine-Tuning with Concurrent Optimization for OOD Generalization and Open-Set OOD Detection. CoRR abs/2405.16417 (2024) - [i12]Qiao Sun, Liujia Yang, Minghao Ma, Nanyang Ye, Qinying Gu:
MiniConGTS: A Near Ultimate Minimalist Contrastive Grid Tagging Scheme for Aspect Sentiment Triplet Extraction. CoRR abs/2406.11234 (2024) - 2023
- [i11]Xilong Zhao, Siyuan Bian, Yaoyun Zhang, Yuliang Zhang, Qinying Gu, Xinbing Wang, Chenghu Zhou, Nanyang Ye:
Domain Invariant Learning for Gaussian Processes and Bayesian Exploration. CoRR abs/2312.11318 (2023) - 2022
- [i10]Runpeng Yu, Hong Zhu, Kaican Li, Lanqing Hong, Rui Zhang, Nanyang Ye, Shao-Lun Huang, Xiuqiang He:
Regularization Penalty Optimization for Addressing Data Quality Variance in OoD Algorithms. CoRR abs/2206.05749 (2022) - [i9]Nanyang Ye, Jingbiao Mei, Zhicheng Fang, Yuwen Zhang, Ziqing Zhang, Huaying Wu, Xiaoyao Liang:
BayesFT: Bayesian Optimization for Fault Tolerant Neural Network Architecture. CoRR abs/2210.01795 (2022) - 2021
- [i8]Nanyang Ye, Kaican Li, Lanqing Hong, Haoyue Bai, Yiting Chen, Fengwei Zhou, Zhenguo Li:
OoD-Bench: Benchmarking and Understanding Out-of-Distribution Generalization Datasets and Algorithms. CoRR abs/2106.03721 (2021) - [i7]Karl Chahine, Nanyang Ye, Hyeji Kim:
DeepIC: Coding for Interference Channels via Deep Learning. CoRR abs/2108.06028 (2021) - [i6]Haoyue Bai, Fengwei Zhou, Lanqing Hong, Nanyang Ye, S.-H. Gary Chan, Zhenguo Li:
NAS-OoD: Neural Architecture Search for Out-of-Distribution Generalization. CoRR abs/2109.02038 (2021) - 2020
- [i5]Shufan Wang, Ningyi Liao, Liyao Xiang, Nanyang Ye, Quanshi Zhang:
Achieving Adversarial Robustness via Sparsity. CoRR abs/2009.05423 (2020) - [i4]Xiao-Yun Zhou, Jiacheng Sun, Nanyang Ye, Xu Lan, Qijun Luo, Bo-Lin Lai, Pedro M. Esperança, Guang-Zhong Yang, Zhenguo Li:
Batch Group Normalization. CoRR abs/2012.02782 (2020) - [i3]Nanyang Ye, Qianxiao Li, Xiao-Yun Zhou, Zhanxing Zhu:
Amata: An Annealing Mechanism for Adversarial Training Acceleration. CoRR abs/2012.08112 (2020) - [i2]Haoyue Bai, Rui Sun, Lanqing Hong, Fengwei Zhou, Nanyang Ye, Han-Jia Ye, S.-H. Gary Chan, Zhenguo Li:
DecAug: Out-of-Distribution Generalization via Decomposed Feature Representation and Semantic Augmentation. CoRR abs/2012.09382 (2020) - 2017
- [i1]Nanyang Ye, Zhanxing Zhu, Rafal K. Mantiuk:
Langevin Dynamics with Continuous Tempering for High-dimensional Non-convex Optimization. CoRR abs/1703.04379 (2017)
Coauthor Index
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