3 papers
math.OC2026
Subspace accelerated measure transport methods for fast and scalable sequential experimental design, with application to photoacoustic imaging
Tiangang Cui, Karina Koval, Roland Herzog +1
We propose a novel approach for sequential optimal experimental design (sOED) for Bayesian inverse problems involving expensive models with high-dimensional unknown parameters. Thi…
stat.ML2026
FLUID: Flow-based Unified Inference for Dynamics
Tiangang Cui, Xiaodong Feng, Chenlong Pei +2
Bayesian filtering and smoothing for high-dimensional nonlinear dynamical systems are fundamental yet challenging problems in many areas of science and engineering. In this work, w…
cs.CE2026
Multiscale Structural Reliability Analysis in high dimensions with Tensor Trains and Physics-Augmented Neural Networks
Aryan Tyagi, Alex de Beer, Tiangang Cui +1
Structural reliability evaluation for composites constitutes a fundamentally high-dimensional multiscale problem, as microscale material uncertainties must propagate to the macrosc…