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Inferring the Langevin Equation with Uncertainty via Bayesian Neural Networks
2 February 2024
Youngkyoung Bae
Seungwoong Ha
Hawoong Jeong
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Papers citing
"Inferring the Langevin Equation with Uncertainty via Bayesian Neural Networks"
17 / 17 papers shown
Learning Stochastic Thermodynamics Directly from Correlation and Trajectory-Fluctuation Currents
Jinghao Lyu
Kyle J. Ray
James P. Crutchfield
AI4CE
220
3
0
26 Apr 2025
Interpretable Machine Learning in Physics: A Review
Sebastian Johann Wetzel
Seungwoong Ha
Raban Iten
Miriam Klopotek
Ziming Liu
AI4CE
395
12
0
30 Mar 2025
A Primer on Bayesian Neural Networks: Review and Debates
Federico Danieli
Konstantinos Pitas
M. Vladimirova
Vincent Fortuin
BDL
AAML
280
35
0
28 Sep 2023
How Tempering Fixes Data Augmentation in Bayesian Neural Networks
International Conference on Machine Learning (ICML), 2022
Gregor Bachmann
Lorenzo Noci
Thomas Hofmann
BDL
AAML
268
11
0
27 May 2022
GradDiv: Adversarial Robustness of Randomized Neural Networks via Gradient Diversity Regularization
Sungyoon Lee
Hoki Kim
Jaewook Lee
AAML
249
69
0
06 Jul 2021
Machine Learning Force Fields
Oliver T. Unke
Stefan Chmiela
H. E. Sauceda
M. Gastegger
I. Poltavsky
Kristof T. Schütt
A. Tkatchenko
K. Müller
AI4CE
330
1,147
0
14 Oct 2020
Hands-on Bayesian Neural Networks -- a Tutorial for Deep Learning Users
IEEE Computational Intelligence Magazine (IEEE CIM), 2020
Laurent Valentin Jospin
Wray Buntine
F. Boussaïd
Hamid Laga
Bennamoun
OOD
BDL
UQCV
558
783
0
14 Jul 2020
Detection of Gravitational Waves Using Bayesian Neural Networks
Yu-Chiung Lin
Jiun-Huei Proty Wu
221
29
0
08 Jul 2020
Learning entropy production via neural networks
Physical Review Letters (PRL), 2020
Dong-Kyum Kim
Youngkyoung Bae
Sangyun Lee
Hawoong Jeong
328
46
0
09 Mar 2020
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning
International Conference on Learning Representations (ICLR), 2020
Arsenii Ashukha
Alexander Lyzhov
Dmitry Molchanov
Dmitry Vetrov
UQCV
FedML
498
344
0
15 Feb 2020
Uncertainty Quantification with Statistical Guarantees in End-to-End Autonomous Driving Control
IEEE International Conference on Robotics and Automation (ICRA), 2019
Rhiannon Michelmore
Matthew Wicker
Luca Laurenti
L. Cardelli
Y. Gal
Marta Z. Kwiatkowska
BDL
277
116
0
21 Sep 2019
A Simple Baseline for Bayesian Uncertainty in Deep Learning
Wesley J. Maddox
T. Garipov
Pavel Izmailov
Dmitry Vetrov
A. Wilson
BDL
UQCV
700
910
0
07 Feb 2019
Adversarial Uncertainty Quantification in Physics-Informed Neural Networks
Journal of Computational Physics (JCP), 2018
Jianlong Wu
P. Perdikaris
AI4CE
PINN
311
394
0
09 Nov 2018
Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network
Xuanqing Liu
Yao Li
Chongruo Wu
Cho-Jui Hsieh
AAML
OOD
294
181
0
01 Oct 2018
Variational Inference: A Review for Statisticians
David M. Blei
A. Kucukelbir
Jon D. McAuliffe
BDL
1.7K
5,306
0
04 Jan 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
International Conference on Machine Learning (ICML), 2015
Y. Gal
Zoubin Ghahramani
UQCV
BDL
2.5K
10,703
0
06 Jun 2015
Adam: A Method for Stochastic Optimization
International Conference on Learning Representations (ICLR), 2014
Diederik P. Kingma
Jimmy Ba
ODL
4.7K
161,471
0
22 Dec 2014
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