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Inferring the Langevin Equation with Uncertainty via Bayesian Neural Networks

Inferring the Langevin Equation with Uncertainty via Bayesian Neural Networks

2 February 2024
Youngkyoung Bae
Seungwoong Ha
Hawoong Jeong
ArXivPDFHTML

Papers citing "Inferring the Langevin Equation with Uncertainty via Bayesian Neural Networks"

3 / 3 papers shown
Title
Learning Stochastic Thermodynamics Directly from Correlation and Trajectory-Fluctuation Currents
Learning Stochastic Thermodynamics Directly from Correlation and Trajectory-Fluctuation Currents
Jinghao Lyu
Kyle J. Ray
James P. Crutchfield
AI4CE
38
1
0
26 Apr 2025
Interpretable Machine Learning in Physics: A Review
Interpretable Machine Learning in Physics: A Review
Sebastian Johann Wetzel
Seungwoong Ha
Raban Iten
Miriam Klopotek
Ziming Liu
AI4CE
50
0
0
30 Mar 2025
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
232
8,157
0
06 Jun 2015
1