Ye, Nanyang

24 publications

ICLR 2026 Unleashing LLMs in Bayesian Optimization: Preference-Guided Framework for Scientific Discovery Xinzhe Yuan, Zhuo Chen, Jianshu Zhang, Huan Xiong, Nanyang Ye, Yuqiang Li, Qinying Gu

NeurIPS 2025 $\Delta \mathrm{Energy}$: Optimizing Energy Change During Vision-Language Alignment Improves Both OOD Detection and OOD Generalization Lin Zhu, Yifeng Yang, Xinbing Wang, Qinying Gu, Nanyang Ye

CVPR 2025 Decision SpikeFormer: Spike-Driven Transformer for Decision Making Wei Huang, Qinying Gu, Nanyang Ye

ICML 2025 Generalizable Multi-Camera 3D Object Detection from a Single Source via Fourier Cross-View Learning Xue Zhao, Qinying Gu, Xinbing Wang, Chenghu Zhou, Nanyang Ye

NeurIPS 2025 Less Is More: An Attention-Free Sequence Prediction Modeling for Offline Embodied Learning Wei Huang, Jianshu Zhang, Leiyu Wang, Heyue Li, Luoyi Fan, Yichen Zhu, Nanyang Ye, Qinying Gu

ICLR 2025 Less Is More: Masking Elements in Image Condition Features Avoids Content Leakages in Style Transfer Diffusion Models Lin Zhu, Xinbing Wang, Chenghu Zhou, Qinying Gu, Nanyang Ye

CVPR 2025 OODD: Test-Time Out-of-Distribution Detection with Dynamic Dictionary Yifeng Yang, Lin Zhu, Zewen Sun, Hengyu Liu, Qinying Gu, Nanyang Ye

ICML 2024 CRoFT: Robust Fine-Tuning with Concurrent Optimization for OOD Generalization and Open-Set OOD Detection Lin Zhu, Yifeng Yang, Qinying Gu, Xinbing Wang, Chenghu Zhou, Nanyang Ye

AAAI 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

AAAI 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

AAAI 2023 Bayesian Cross-Modal Alignment Learning for Few-Shot Out-of-Distribution Generalization Lin Zhu, Xinbing Wang, Chenghu Zhou, Nanyang Ye

AAAI 2023 Certifiable Out-of-Distribution Generalization Nanyang Ye, Lin Zhu, Jia Wang, Zhaoyu Zeng, Jiayao Shao, Chensheng Peng, Bikang Pan, Kaican Li, Jun Zhu

MLJ 2022 Achieving Adversarial Robustness via Sparsity Ningyi Liao, Shufan Wang, Liyao Xiang, Nanyang Ye, Shuo Shao, Pengzhi Chu

CVPR 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

AAAI 2022 OoDHDR-Codec: Out-of-Distribution Generalization for HDR Image Compression Linfeng Cao, Aofan Jiang, Wei Li, Huaying Wu, Nanyang Ye

AAAI 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

CVPR 2021 Adversarial Invariant Learning Nanyang Ye, Jingxuan Tang, Huayu Deng, Xiao-Yun Zhou, Qianxiao Li, Zhenguo Li, Guang-Zhong Yang, Zhanxing Zhu

AAAI 2021 Amata: An Annealing Mechanism for Adversarial Training Acceleration Nanyang Ye, Qianxiao Li, Xiao-Yun Zhou, Zhanxing Zhu

AAAI 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

ICCV 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

CVPR 2019 Predicting Visible Image Differences Under Varying Display Brightness and Viewing Distance Nanyang Ye, Krzysztof Wolski, Rafal K. Mantiuk

NeurIPS 2018 Bayesian Adversarial Learning Nanyang Ye, Zhanxing Zhu

IJCAI 2018 Stochastic Fractional Hamiltonian Monte Carlo Nanyang Ye, Zhanxing Zhu

NeurIPS 2017 Langevin Dynamics with Continuous Tempering for Training Deep Neural Networks Nanyang Ye, Zhanxing Zhu, Rafal Mantiuk