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Probabilistic Meshless Methods on Manifolds

Paper recorded by Signals 4 on 2026-10-29 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-29 on arXiv · recorded by Signals 4 on 2026-10-30

Category: cs.LG · 机器学习 · first seen 2026-10-30

Abstract

Probabilistic meshless methods solve partial differential equations (PDEs) by placing a Gaussian process prior on the solution and conditioning it on the PDE at a finite set of collocation nodes. The posterior provides both an approximation of the solution and a Bayesian quantification of its error. While these methods are well established on Euclidean domains, their extension to manifolds lacks,

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#132 most recent of 737 cs.LG papers we have recorded · ↑ newer: Turing LLM Post-Training: Calibrated Distillation and Efficient Dynami · ↓ older: Attention, Dynamic Wave and Hybrid Sequence Mixers in Language Models
Cite this page: Probabilistic Meshless Methods on Manifolds: the #132 most recent of 737 cs.LG papers we have recorded (as of 2026-10-29). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/probabilistic-meshless-methods-on-manifolds.html
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