32 citations · 37 across the 10 of their papers we have counts for
3 papers · 1 filter
In-context learning to predict critical transitions in dynamical systems
Yunus Sevinchan, Juan Nathaniel, Kai Ueltzhöffer +8
Critical transitions - abrupt, often irreversible changes in system dynamics - arise across human and natural systems, often with catastrophic consequences. Real-world observations…
Universal Neural Optimal Transport
Jonathan Geuter, Gregor Kornhardt, Ingimar Tomasson +1
Optimal Transport (OT) problems are a cornerstone of many applications, but solving them is computationally expensive. To address this problem, we propose UNOT (Universal Neural Op…
Training Generative Networks with general Optimal Transport distances
Vaios Laschos, Jan Tinapp, Klaus Obermayer
We propose a new algorithm that uses an auxiliary neural network to express the potential of the optimal transport map between two data distributions. In the sequel, we use the afo…