2 papers
cs.LG2026
Conformalized Quantum DeepONet Ensembles for Scalable Operator Learning with Distribution-Free Uncertainty
Purav Matlia, Christian Moya, Guang Lin
Operator learning enables fast surrogate modeling of high-dimensional dynamical systems, but existing approaches face two fundamental limitations: quadratic inference complexity an…
q-fin.MF2025
Data-driven Feynman-Kac Discovery with Applications to Prediction and Data Generation
Qi Feng, Guang Lin, Purav Matlia +1
In this paper, we propose a novel data-driven framework for discovering probabilistic laws underlying the Feynman-Kac formula. Specifically, we introduce the first stochastic SINDy…