2 citations · 2 across the 2 of their papers we have counts for
4 papers
Finite Expression Method with TranNet-based Function Learning for High-Dimensional Partial Differential Equations
Phuoc-Toan Huynh, Feng Bao, Haizhao Yang +1
In this paper, we study a machine-learning-based solver for high-dimensional partial differential equations (PDEs). Computing accurate solutions efficiently for such problems remai…
A Score Filter Enhanced Data Assimilation Framework for Data-Driven Dynamical Systems
Jingqiao Tang, Ryan Bausback, Feng Bao +2
We introduce a score-filter-enhanced data assimilation framework designed to reduce predictive uncertainty in machine learning (ML) models for data-driven dynamical system forecast…
Stochastic Operator Network: A Stochastic Maximum Principle Based Approach to Operator Learning
Ryan Bausback, Jingqiao Tang, Lu Lu +2
We develop a novel framework for uncertainty quantification in operator learning, the Stochastic Operator Network (SON). SON combines the stochastic optimal control concepts of the…
Federated Learning on Stochastic Neural Networks
Jingqiao Tang, Ryan Bausback, Feng Bao +1
Federated learning is a machine learning paradigm that leverages edge computing on client devices to optimize models while maintaining user privacy by ensuring that local data rema…