3 papers
cs.LG2025
FA-INR: Adaptive Implicit Neural Representations for Interpretable Exploration of Simulation Ensembles
Ziwei Li, Yuhan Duan, Tianyu Xiong +3
Surrogate models are essential for efficient exploration of large-scale ensemble simulations. Implicit neural representations (INRs) provide a compact and continuous framework for…
stat.ML2025
ConfEviSurrogate: A Conformalized Evidential Surrogate Model for Uncertainty Quantification
Yuhan Duan, Xin Zhao, Neng Shi +1
Surrogate models, crucial for approximating complex simulation data across sciences, inherently carry uncertainties that range from simulation noise to model prediction errors. Wit…
cs.LG2024
SurroFlow: A Flow-Based Surrogate Model for Parameter Space Exploration and Uncertainty Quantification
Jingyi Shen, Yuhan Duan, Han-Wei Shen
Existing deep learning-based surrogate models facilitate efficient data generation, but fall short in uncertainty quantification, efficient parameter space exploration, and reverse…