15 citations · 43 across the 12 of their papers we have counts for
Showing 2021 · cs.LGShow all
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cs.LG2021★ 1 cited
Low-Dimensional State and Action Representation Learning with MDP Homomorphism Metrics
Nicolò Botteghi, Mannes Poel, Beril Sirmacek +1
Deep Reinforcement Learning has shown its ability in solving complicated problems directly from high-dimensional observations. However, in end-to-end settings, Reinforcement Learni…
cs.LG2021★ 11 cited
Learning normal form autoencoders for data-driven discovery of universal,parameter-dependent governing equations
Manu Kalia, Steven L. Brunton, Hil G. E. Meijer +2
Complex systems manifest a small number of instabilities and bifurcations that are canonical in nature, resulting in universal pattern forming characteristics as a function of some…