Jingyue Shi — accepted AI-conference papers

2025

Learning Robust Neural Processes with Risk-Averse Stochastic Optimization

Huafeng Liu, Yiran Fu, Liping Jing, Hui Li, Shuyang Lin, Jingyue Shi +2

ICML 2025poster

Neural processes (NPs) are a promising paradigm to enable skill transfer learning across tasks with the aid of the distribution of functions. The previous NPs employ the empirical risk minimization principle in optimization. However, the fast adaption ability to different tasks can vary widely, and…

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2025

Learning to Generalize: An Information Perspective on Neural Processes

Hui Li, Huafeng Liu, Shuyang Lin, Jingyue Shi, Yiran Fu, Liping Jing

NeurIPS 2025poster

Neural Processes (NPs) combine the adaptability of neural networks with the efficiency of meta-learning, offering a powerful framework for modeling stochastic processes. However, existing methods focus on empirical performance while lacking a rigorous theoretical understanding of generalization. To…

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