arXiv Machine Learning August 11, 2026 By Konrad Kleinberg, Thomas Kruse

Walk-on-Spheres Monte Carlo and deep neural network approximations of elliptic PDEs with drift and killing

Read the original on arXiv Machine Learning →

arXiv:2608. 09494v1 Announce Type: cross Abstract: In this paper we provide Monte Carlo and deep neural network approximations for stochastic representations of solutions to linear elliptic partial differential equations with constant diffusion, drift and killing.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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