2 papers
cs.LG2025
Weight-Parameterization in Continuous Time Deep Neural Networks for Surrogate Modeling
Haley Rosso, Lars Ruthotto, Khachik Sargsyan
Continuous-time deep learning models, such as neural ordinary differential equations (ODEs), offer a promising framework for surrogate modeling of complex physical systems. A centr…
stat.ML2025
Efficient Neural Network Approaches for Conditional Optimal Transport with Applications in Bayesian Inference
Zheyu Oliver Wang, Ricardo Baptista, Youssef Marzouk +2
We present two neural network approaches that approximate the solutions of static and dynamic $\unicode{x1D450}\unicode{x1D45C}\unicode{x1D45B}\unicode{x1D451}\unicode{x1D456}\unic…