Stochastic Differential Equations

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Period ending 2026-09-21

8 new papers

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Period ending 2026-09-14

10 new papers

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Period ending 2026-09-07

3 new papers

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252 papers

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  1. Deep Operator BSDE: a Numerical Scheme to Approximate Solution Operators

    Dec 4, 2024Pere Diaz-Lozano, Giulia Di NunnoStochastic Differential EquationsClassical Numerical Solver

  2. Polynomial Scaling is Possible For Neural Operator Approximations of Structured Families of BSDEs

    Oct 18, 2024Takashi Furuya, Anastasis KratsiosNeural OperatorsLogarithmic Sobolev Inequalities

  3. Discrete distributions are learnable from metastable samples

    Oct 17, 2024Abhijith Jayakumar, Andrey Y. Lokhov, Sidhant Misra +1Two-Dimensional Ising ModelDistributional Learning

  4. Brownian Motion with a Pulse: A Biostatistician's Guide to Diffusions, Bridges, Functional PCA, and First-Passage Models

    Aug 16, 2024Eliuvish Han CuiStochastic Differential EquationsTime-To-Event Data

  5. Accelerated Stochastic Min-Max Optimization Based on Bias-corrected Momentum

    Jun 18, 2024Haoyuan Cai, Sulaiman A. Alghunaim, Ali H. SayedStochastic Smooth Convex OptimizationConvex Optimization

  6. Stable Neural Stochastic Differential Equations in Analyzing Irregular Time Series Data

    Feb 22, 2024YongKyung Oh, Dong-Young Lim, Sungil KimNeural Ordinary Differential EquationsStochastic Differential Equations

  7. Topology-Guided Modular Actor-Critic Learning for Continuous Systems under Temporal Objectives

    Apr 20, 2023Lening Li, Zhentian Qian, Jianan Xia +7Soft Actor-CriticModel-Free Reinforcement Learning

  8. Spectral Diffusion Processes

    Sep 28, 2022Angus Phillips, Thomas Seror, Michael Hutchinson +3Diffusion ProcessesStochastic Systems

  9. Learning Non-Vacuous Generalization Bounds from Optimization

    Jun 9, 2022Chengli Tan, Jiangshe Zhang, Junmin Liu +1Generalization BoundsStochastic Gradient Descent

  10. XConv: Low-memory stochastic backpropagation for convolutional layers

    Jun 13, 2021Anirudh Thatipelli, Jeffrey Sam, Mathias Louboutin +3ConvolutionalBackpropagation

  11. Deep learning based numerical approximation algorithms for stochastic partial differential equations

    Dec 2, 2020Christian Beck, Sebastian Becker, Patrick Cheridito +2Stochastic Differential EquationsNeural-Network Approximation

  12. Fast Convergence for High-Order ODE Solvers in Diffusion Probabilistic Models

    Date pendingDaniel Zhengyu Huang, Jiaoyang Huang, Zhengjiang LinStochastic Differential EquationsClassical Numerical Solver