We always welcome self-motivated students including undergraduate interns, graduate applicants to apply for positions in our lab from various backgrounds, such as mathematics, computer science, software engineering, and automation etc. IEEE Vehicular Technology Conference 2015 (VTC 2015).pp. Efficient Multi-Cell Clustering for Coordinated Multi-Point Transmission with Blossom Tree Algorithm. Nanyang Ye, Linhao Dong, Xiaoming Tao, Ning Ge. International Conference on Image Processing 2016 (ICIP 2016). Mouse Calibration Aided Real-time Gaze Estimation Based on Boost Gaussian Bayesian Learning. Nanyang Ye, Xiaoming Tao, Linhao Dong, Ning Ge. International Conference on Intelligent Robots and Systems 2021 (IROS 2021). VeniBot: Towards Autonomous Venipuncture with Automatic Puncture Area and Angle Regression from NIR Images. Xu Cao, Zijie Chen, Bolin Lai, Yuxuan Wang, Yu Chen, Zhengqing Cao, Zhilin Yang, Nanyang Ye, Junbo Zhao, Xiao-Yun Zhou, Peng Qi. Human Vision and Electronic Imaging 2021 (HVEI 2021). The Effect of Display Brightness and Viewing Distance: A Dataset for Visually Lossless Image Compression. 1718-1722.Īliaksei Mikhailiuk, Nanyang Ye, Rafał K. International Conference on Image Processing 2018 (ICIP 2018). Trained Perceptual Transform for Quality Assessment of High Dynamic Range Images and Video. Picture Coding Symposium 2019 (PCS 2019). Visibility Metric for Visually Lossless Image Compression.
ACM Transaction on Graphics (TOG 2018) (The first three authors contribute equally to the paper). Dataset and Metrics for Predicting Local Visible Differences. Krzysztof Wolski#, Daniele Giunchi#, Nanyang Ye#, Piotr Didyk, Karol Myszkowski, Radosław Mantiuk, Hans-PeterSeidel, Anthony Steed, Rafał K. Design Automation Conference 2021 (DAC 2021). BayesFT: Bayesian Optimization for Fault Tolerant Neural Network Architecture. Nanyang Ye, Jingbiao Mei, Zhicheng Fang, Yuwen Zhang, Ziqing Zhang, Huaying Wu, Xiaoyao Liang. IEEE Conference on Computer Vision and Pattern Recognition 2019 (CVPR 2019). Predicting Visible Image Differences Under Varying Display Brightness and Viewing Distance. International Joint Conference on Artificial Intelligence 2018 (IJCAI 2018). Stochastic Fractional Hamiltonian Monte Carlo. AAAI Conference on Artificial Intelligence (AAAI 2021). Amata: An Annealing Mechanism for Adversarial Training Acceleration. Nanyang Ye, Qianxiao Li, Xiao-Yun Zhou, Zhanxing Zhu. AAAI Conference on Artificial Intelligence 2022 (AAAI 2022). Runpeng Yu, Hong Zhu, Kaican Li, Lanqing Hong, Rui Zhang*, Nanyang Ye*, Shao-Lun Huang, Xiuqiang He. OoDHDR-codec: Out-of-Distribution Generalization for HDR Image Compression. Linfeng Cao, Aofan Jiang, Wei Li, Huaying Wu, Nanyang Ye*. International Conference on Computer Vision 2021 (ICCV 2021). NAS-OoD: Neural Architecture Search for Out-of-Distribution Generalization. Haoyue Bai, Fengwei Zhou, Lanqing Hong, Nanyang Ye*, S.-H. 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, Gary Chan, Zhenguo Li. IEEE Conference on Computer Vision and Pattern Recognition 2021 (CVPR 2021). Nanyang Ye, Jingxuan Tang, Huayu Deng, Xiao-Yun Zhou, Qianxiao Li, Zhenguo Li, Guang-Zhong Yang, Zhanxing Zhu. Advances in Neural Information Processing Systems 2017 (NeurIPS 2017). Langevin Dynamics with Continuous Tempering for Training Deep Neural Networks. Advances in Neural Information Processing Systems 2018 (NeurIPS 2018). IEEE Transaction on Neural Network and Learning System 2021.
An Annealing Mechanism for Adversarial Training. Our lab has published several papers on top machine learning and artificial intelligence conferences, such as NeurIPS, CVPR, ICCV, AAAI, IJCAI, etc.Ĭontact: ynylincoln AT sjtu DOT edu DOT cn Selected Publications I serve as programme committee members and reviewers for several key machine learning journals and conferences. We are devoted to solve the fundamental challenge of the generalization ability of machine learning systems.
My current research interests include but not limited to Bayesian deep learning, causal inference, design and application of deep learning systems. I obtained PhD from University of Cambridge.
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