3 papers
physics.comp-ph2026
A Physics-Informed B-Spline Framework for Continuous Approximation of Flow Data
Junoh Jung, David Lenz, Emil Constantinescu +1
Continuous approximations of flow data are useful for downstream analysis, differentiation, and visualization, but purely data-driven reconstructions do not, in general, preserve t…
physics.flu-dyn2026
Learning Differentiable Weak-Form Corrections to Accelerate Finite Element Simulations
Junoh Jung, Emil Constantinescu
We present a differentiable weak-form learning approach for accelerating finite element simulations. Rather than introducing black-box source terms in the strong form of the govern…
stat.ML2025
Distributional Sensitivity Analysis: Enabling Differentiability in Sample-Based Inference
Pi-Yueh Chuang, Ahmed Attia, Emil Constantinescu
This work introduces a mathematical framework for estimating the space-parameter sensitivity of random samples in arbitrary dimensions. Such sensitivity effectively acts as gradien…