Nanyang Ye

According to our database, Nanyang Ye authored at least 34 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

PNAS-MOT: Multi-Modal Object Tracking with Pareto Neural Architecture Search.

Chensheng Peng, Zhaoyu Zeng, Jinling Gao, Jundong Zhou, Masayoshi Tomizuka, Xinbing Wang, Chenghu Zhou, Nanyang Ye

CoRR, 2024

Rethinking ASTE: A Minimalist Tagging Scheme Alongside Contrastive Learning.

Qiao Sun, Liujia Yang, Minghao Ma, Nanyang Ye, Qinying Gu

CoRR, 2024

AceMap: Knowledge Discovery through Academic Graph.

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

CoRR, 2024

Domain Invariant Learning for Gaussian Processes and Bayesian Exploration.

Xilong Zhao, Siyuan Bian, Yaoyun Zhang, Yuliang Zhang, Qinying Gu, Xinbing Wang, Chenghu Zhou, Nanyang Ye

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

G-NAS: Generalizable Neural Architecture Search for Single Domain Generalization Object Detection.

Fan Wu, Jinling Gao, Lanqing Hong, Xinbing Wang, Chenghu Zhou, Nanyang Ye

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

An Annealing Mechanism for Adversarial Training Acceleration.

Nanyang Ye, Qianxiao Li, Xiao-Yun Zhou, Zhanxing Zhu

IEEE Trans. Neural Networks Learn. Syst., February, 2023

Bayesian Cross-Modal Alignment Learning for Few-Shot Out-of-Distribution Generalization.

Lin Zhu, Xinbing Wang, Chenghu Zhou, Nanyang Ye

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Certifiable Out-of-Distribution Generalization.

Nanyang Ye, Lin Zhu, Jia Wang, Zhaoyu Zeng, Jiayao Shao, Chensheng Peng, Bikang Pan, Kaican Li, Jun Zhu

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Achieving adversarial robustness via sparsity.

Ningyi Liao, Shufan Wang, Liyao Xiang, Nanyang Ye, Shuo Shao, Pengzhi Chu

Mach. Learn., 2022

OoD-Bench: Quantifying and Understanding Two Dimensions of Out-of-Distribution Generalization.

Nanyang Ye, Kaican Li, Haoyue Bai, Runpeng Yu, Lanqing Hong, Fengwei Zhou, Zhenguo Li, Jun Zhu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Regularization Penalty Optimization for Addressing Data Quality Variance in OoD Algorithms.

Runpeng Yu, Hong Zhu, Kaican Li, Lanqing Hong, Rui Zhang, Nanyang Ye, Shao-Lun Huang, Xiuqiang He

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

OoDHDR-Codec: Out-of-Distribution Generalization for HDR Image Compression.

Linfeng Cao, Aofan Jiang, Wei Li, Huaying Wu, Nanyang Ye

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

OoD-Bench: Benchmarking and Understanding Out-of-Distribution Generalization Datasets and Algorithms.

Nanyang Ye, Kaican Li, Lanqing Hong, Haoyue Bai, Yiting Chen, Fengwei Zhou, Zhenguo Li

CoRR, 2021

Semi-supervised Vein Segmentation of Ultrasound Images for Autonomous Venipuncture.

Yu Chen, Yuxuan Wang, Bolin Lai, Zijie Chen, Xu Cao, Nanyang Ye, Zhongyuan Ren, Junbo Zhao, Xiao-Yun Zhou, Peng Qi

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

NAS-OoD: Neural Architecture Search for Out-of-Distribution Generalization.

Haoyue Bai, Fengwei Zhou, Lanqing Hong, Nanyang Ye, S.-H. Gary Chan, Zhenguo Li

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

The effect of display brightness and viewing distance: a dataset for visually lossless image compression.

Aliaksei Mikhailiuk, Nanyang Ye, Rafal K. Mantiuk

Proceedings of the Human Vision and Electronic Imaging 2021, Virtual Event, January 2021., 2021

DeepIC: Coding for Interference Channels via Deep Learning.

Karl Chahine, Nanyang Ye, Hyeji Kim

Proceedings of the IEEE Global Communications Conference, 2021

BayesFT: Bayesian Optimization for Fault Tolerant Neural Network Architecture.

Nanyang Ye, Jingbiao Mei, Zhicheng Fang, Yuwen Zhang, Ziqing Zhang, Huaying Wu, Xiaoyao Liang

Proceedings of the 58th ACM/IEEE Design Automation Conference, 2021

Adversarial Invariant Learning.

Nanyang Ye, Jingxuan Tang, Huayu Deng, Xiao-Yun Zhou, Qianxiao Li, Zhenguo Li, Guang-Zhong Yang, Zhanxing Zhu

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Amata: An Annealing Mechanism for Adversarial Training Acceleration.

Nanyang Ye, Qianxiao Li, Xiao-Yun Zhou, Zhanxing Zhu

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

DecAug: Out-of-Distribution Generalization via Decomposed Feature Representation and Semantic Augmentation.

Haoyue Bai, Rui Sun, Lanqing Hong, Fengwei Zhou, Nanyang Ye, Han-Jia Ye, S.-H. Gary Chan, Zhenguo Li

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Visibility metrics and their applications in visually lossless image compression.

Nanyang Ye

PhD thesis, 2020

Batch Group Normalization.

Xiao-Yun Zhou, Jiacheng Sun, Nanyang Ye, Xu Lan, Qijun Luo, Bo-Lin Lai, Pedro M. Esperança, Guang-Zhong Yang, Zhenguo Li

CoRR, 2020

Achieving Adversarial Robustness via Sparsity.

Shufan Wang, Ningyi Liao, Liyao Xiang, Nanyang Ye, Quanshi Zhang

CoRR, 2020

2019

Visibility Metric for Visually Lossless Image Compression.

Nanyang Ye, María Pérez-Ortiz, Rafal K. Mantiuk

Proceedings of the Picture Coding Symposium, 2019

Predicting Visible Image Differences Under Varying Display Brightness and Viewing Distance.

Nanyang Ye, Krzysztof Wolski, Rafal K. Mantiuk

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Dataset and Metrics for Predicting Local Visible Differences.

Krzysztof Wolski, Daniele Giunchi, Nanyang Ye, Piotr Didyk, Karol Myszkowski, Radoslaw Mantiuk, Hans-Peter Seidel, Anthony Steed, Rafal K. Mantiuk

ACM Trans. Graph., 2018

Bayesian Adversarial Learning.

Nanyang Ye, Zhanxing Zhu

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Stochastic Fractional Hamiltonian Monte Carlo.

Nanyang Ye, Zhanxing Zhu

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Trained Perceptual Transform for Quality Assessment of High Dynamic Range Images and Video.

Nanyang Ye, María Pérez-Ortiz, Rafal K. Mantiuk

Proceedings of the 2018 IEEE International Conference on Image Processing, 2018

2017

Langevin Dynamics with Continuous Tempering for High-dimensional Non-convex Optimization.

Nanyang Ye, Zhanxing Zhu, Rafal K. Mantiuk

CoRR, 2017

Langevin Dynamics with Continuous Tempering for Training Deep Neural Networks.

Nanyang Ye, Zhanxing Zhu, Rafal Mantiuk

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

Mouse calibration aided real-time gaze estimation based on boost Gaussian Bayesian learning.

Nanyang Ye, Xiaoming Tao, Linhao Dong, Ning Ge

Proceedings of the 2016 IEEE International Conference on Image Processing, 2016

2015

Efficient Multi-Cell Clustering for Coordinated Multi-Point Transmission with Blossom Tree Algorithm.

Nanyang Ye, Linhao Dong, Xiaoming Tao, Ning Ge

Proceedings of the IEEE 82nd Vehicular Technology Conference, 2015