270 citations · 618 across the 36 of their papers we have counts for
4 papers · 1 filter
Operator inference with roll outs for learning reduced models from scarce and low-quality data
Wayne Isaac Tan Uy, Dirk Hartmann, Benjamin Peherstorfer
Data-driven modeling has become a key building block in computational science and engineering. However, data that are available in science and engineering are typically scarce, oft…
An Extensible Benchmark Suite for Learning to Simulate Physical Systems
Karl Otness, Arvi Gjoka, Joan Bruna +4
Simulating physical systems is a core component of scientific computing, encompassing a wide range of physical domains and applications. Recently, there has been a surge in data-dr…
Active operator inference for learning low-dimensional dynamical-system models from noisy data
Wayne Isaac Tan Uy, Yuepeng Wang, Yuxiao Wen +1
Noise poses a challenge for learning dynamical-system models because already small variations can distort the dynamics described by trajectory data. This work builds on operator in…
Operator inference of non-Markovian terms for learning reduced models from partially observed state trajectories
Wayne Isaac Tan Uy, Benjamin Peherstorfer
This work introduces a non-intrusive model reduction approach for learning reduced models from partially observed state trajectories of high-dimensional dynamical systems. The prop…