43 citations · 81 across the 2 of their papers we have counts for
3 papers
physics.comp-ph2020
Solver-in-the-Loop: Learning from Differentiable Physics to Interact with Iterative PDE-Solvers
Kiwon Um, Robert Brand, Yun +3
Finding accurate solutions to partial differential equations (PDEs) is a crucial task in all scientific and engineering disciplines. It has recently been shown that machine learnin…
cs.LG2020★ 43 cited
Learning to Control PDEs with Differentiable Physics
Philipp Holl, Vladlen Koltun, Nils Thuerey
Predicting outcomes and planning interactions with the physical world are long-standing goals for machine learning. A variety of such tasks involves continuous physical systems, wh…
physics.ins-det2019★ 38 cited
Deep learning based pulse shape discrimination for germanium detectors
P. Holl, L. Hauertmann, B. Majorovits +3
Experiments searching for rare processes like neutrinoless double beta decay heavily rely on the identification of background events to reduce their background level and increase t…