Contrastive Conditional Neural Processes. - Zesheng Ye; Lina Yao 001 (CVPR, 2022)

Socially-aware Dual Contrastive Learning for Cold-Start Recommendation. - Jing Du 003; Zesheng Ye; Lina Yao 001; Bin Guo 001; Zhiwen Yu 001 (SIGIR, 2022)

See What You See: Self-supervised Cross-modal Retrieval of Visual Stimuli from Brain Activity. - Zesheng Ye; Lina Yao 001; Yu Zhang; Sylvia Gustin (CoRR, 2022)

NP-SSL: A Modular and Extensible Self-supervised Learning Library with Neural Processes. - Zesheng Ye; Jing Du 003; Yao Liu 017; Yihong Zhang 001; Lina Yao 001 (CIKM, 2023)

Distributional Domain-Invariant Preference Matching for Cross-Domain Recommendation. - Jing Du 003; Zesheng Ye; Bin Guo 001; Zhiwen Yu 001; Lina Yao 001 (ICDM, 2023)

IDNP: Interest Dynamics Modeling Using Generative Neural Processes for Sequential Recommendation. - Jing Du 003; Zesheng Ye; Bin Guo 001; Zhiwen Yu 001; Lina Yao 001 (WSDM, 2023)

Uncertainty-Aware Pedestrian Trajectory Prediction via Distributional Diffusion. - Yao Liu 017; Zesheng Ye; Binghao Li; Lina Yao 001 (CoRR, 2023)

Adversarially Contrastive Estimation of Conditional Neural Processes. - Zesheng Ye; Jing Du 003; Lina Yao 001 (CoRR, 2023)

Sample-specific Masks for Visual Reprogramming-based Prompting. - Chengyi Cai; Zesheng Ye; Lei Feng 006; Jianzhong Qi 001; Feng Liu 003 (ICML, 2024)

Bayesian-guided Label Mapping for Visual Reprogramming. - Chengyi Cai; Zesheng Ye; Lei Feng 006; Jianzhong Qi 001; Feng Liu 003 (NeurIPS, 2024)

Identifiability of Cross-Domain Recommendation via Causal Subspace Disentanglement. - Jing Du 003; Zesheng Ye; Bin Guo 001; Zhiwen Yu 001; Lina Yao 001 (SIGIR, 2024)

Joint Identifiability of Cross-Domain Recommendation via Hierarchical Subspace Disentanglement. - Jing Du 003; Zesheng Ye; Bin Guo 001; Zhiwen Yu 001; Lina Yao 001 (CoRR, 2024)

Towards Robust Cross-Domain Recommendation with Joint Identifiability of User Preference. - Jing Du 003; Zesheng Ye; Bin Guo 001; Zhiwen Yu 001; Jia Wu 001; Jian Yang 001; Michael Sheng 001; Lina Yao 001 (CoRR, 2024)

Uncertainty-aware pedestrian trajectory prediction via distributional diffusion. - Yao Liu 017; Zesheng Ye; Rui Wang 088; Binghao Li; Quan Z. Sheng; Lina Yao 001 (Knowl. Based Syst., 2024)

Self-supervised cross-modal visual retrieval from brain activities. - Zesheng Ye; Lina Yao 001; Yu Zhang; Sylvia Gustin (Pattern Recognit., 2024)

Attribute-based Visual Reprogramming for Vision-Language Models. - Chengyi Cai; Zesheng Ye; Lei Feng 006; Jianzhong Qi 001; Feng Liu 003 (ICLR, 2025)

Attribute-based Visual Reprogramming for Image Classification with CLIP. - Chengyi Cai; Zesheng Ye; Lei Feng 006; Jianzhong Qi 001; Feng Liu 003 (CoRR, 2025)

Membership Inference Attack Should Move On to Distributional Statistics for Distilled Generative Models. - Muxing Li; Zesheng Ye; Yixuan Li 001; Andy Song; Guangquan Zhang 001; Feng Liu 003 (CoRR, 2025)

Understanding Model Reprogramming for CLIP via Decoupling Visual Prompts. - Chengyi Cai; Zesheng Ye; Lei Feng 006; Jianzhong Qi 001; Feng Liu 003 (CoRR, 2025)

Neural Network Reprogrammability: A Unified Theme on Model Reprogramming, Prompt Tuning, and Prompt Instruction. - Zesheng Ye; Chengyi Cai; Ruijiang Dong; Jianzhong Qi 001; Lei Feng 006; Pin-Yu Chen; Feng Liu 003 (CoRR, 2025)

Sample-Specific Noise Injection For Diffusion-Based Adversarial Purification. - Yuhao Sun; Jiacheng Zhang; Zesheng Ye; Chaowei Xiao; Feng Liu (CoRR, 2025)