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Bayesian Spline Learning for Equation Discovery of Nonlinear Dynamics
  with Quantified Uncertainty

Bayesian Spline Learning for Equation Discovery of Nonlinear Dynamics with Quantified Uncertainty

14 October 2022
Luning Sun
Daniel Zhengyu Huang
Hao Sun
Jian-Xun Wang
ArXivPDFHTML

Papers citing "Bayesian Spline Learning for Equation Discovery of Nonlinear Dynamics with Quantified Uncertainty"

3 / 3 papers shown
Title
Monte Carlo Neural PDE Solver for Learning PDEs via Probabilistic Representation
Monte Carlo Neural PDE Solver for Learning PDEs via Probabilistic Representation
Rui Zhang
Qi Meng
Rongchan Zhu
Yue Wang
Wenlei Shi
Shihua Zhang
Zhi-Ming Ma
Tie-Yan Liu
DiffM
AI4CE
51
4
0
10 Feb 2023
Spline-PINN: Approaching PDEs without Data using Fast, Physics-Informed
  Hermite-Spline CNNs
Spline-PINN: Approaching PDEs without Data using Fast, Physics-Informed Hermite-Spline CNNs
Nils Wandel
Michael Weinmann
Michael Neidlin
Reinhard Klein
AI4CE
58
60
0
15 Sep 2021
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
285
9,145
0
06 Jun 2015
1