A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Study large deviations for hypoelliptic diffusion on sub-Riemannian manifolds.
A new method uses deep learning to predict rare events in complex systems.
We generalize classical large deviations theorems to the setting of complete Riemannian manifolds. We prove the analogue of Mogulskii's theorem for geodesic random walks via a general approach using visocity solutions for Hamilton-Jacobi equations. As a corollary, we also obtain the analogue of Cramér's theorem. The ap…
Deep reinforcement learning method finds rare events in complex systems.
New framework embeds generalization in learning dynamics using large deviation theory.