Scientific Computing and Artificial Intelligence

Predictive collective variable discovery with deep Bayesian models for atomistic systems.

Deep residual networks for dimensionality reduction and surrogate modeling in high-dimensional inverse problems

Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs

Uncertainty Quantification of RANS Data-Driven Turbulence Modeling