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HyperSINDy: Deep Generative Modeling of Nonlinear Stochastic Governing
  Equations

HyperSINDy: Deep Generative Modeling of Nonlinear Stochastic Governing Equations

7 October 2023
Mozes Jacobs
Bingni W. Brunton
Steven L. Brunton
J. Nathan Kutz
Ryan V. Raut
ArXivPDFHTML

Papers citing "HyperSINDy: Deep Generative Modeling of Nonlinear Stochastic Governing Equations"

26 / 26 papers shown
Title
Convergence of uncertainty estimates in Ensemble and Bayesian sparse
  model discovery
Convergence of uncertainty estimates in Ensemble and Bayesian sparse model discovery
Liyao (Mars) Gao
Urban Fasel
Steven L. Brunton
J. Nathan Kutz
58
12
0
30 Jan 2023
Bayesian Spline Learning for Equation Discovery of Nonlinear Dynamics
  with Quantified Uncertainty
Bayesian Spline Learning for Equation Discovery of Nonlinear Dynamics with Quantified Uncertainty
Luning Sun
Daniel Zhengyu Huang
Hao Sun
Jian-Xun Wang
59
10
0
14 Oct 2022
PI-VAE: Physics-Informed Variational Auto-Encoder for stochastic
  differential equations
PI-VAE: Physics-Informed Variational Auto-Encoder for stochastic differential equations
Weiheng Zhong
Hadi Meidani
DRL
62
38
0
21 Mar 2022
PySINDy: A comprehensive Python package for robust sparse system
  identification
PySINDy: A comprehensive Python package for robust sparse system identification
A. Kaptanoglu
Brian M. de Silva
Urban Fasel
Kadierdan Kaheman
Andy J. Goldschmidt
...
Zachary G. Nicolaou
Kathleen P. Champion
Jean-Christophe Loiseau
J. Nathan Kutz
Steven L. Brunton
AI4CE
69
149
0
12 Nov 2021
Physics-Integrated Variational Autoencoders for Robust and Interpretable
  Generative Modeling
Physics-Integrated Variational Autoencoders for Robust and Interpretable Generative Modeling
Naoya Takeishi
Alexandros Kalousis
DRL
AI4CE
64
54
0
25 Feb 2021
Stochastic embeddings of dynamical phenomena through variational
  autoencoders
Stochastic embeddings of dynamical phenomena through variational autoencoders
C. A. García
P. Félix
J. Presedo
A. Otero
BDL
48
2
0
13 Oct 2020
Variational Deep Learning for the Identification and Reconstruction of
  Chaotic and Stochastic Dynamical Systems from Noisy and Partial Observations
Variational Deep Learning for the Identification and Reconstruction of Chaotic and Stochastic Dynamical Systems from Noisy and Partial Observations
Duong Nguyen
Said Ouala
Lucas Drumetz
Ronan Fablet
37
13
0
04 Sep 2020
Dynamical Variational Autoencoders: A Comprehensive Review
Dynamical Variational Autoencoders: A Comprehensive Review
Laurent Girin
Simon Leglaive
Xiaoyu Bie
Julien Diard
Thomas Hueber
Xavier Alameda-Pineda
BDL
81
219
0
28 Aug 2020
Failure Modes of Variational Autoencoders and Their Effects on
  Downstream Tasks
Failure Modes of Variational Autoencoders and Their Effects on Downstream Tasks
Yaniv Yacoby
Weiwei Pan
Finale Doshi-Velez
CML
DRL
57
26
0
14 Jul 2020
Identifying Latent Stochastic Differential Equations
Identifying Latent Stochastic Differential Equations
Ali Hasan
João M. Pereira
Sina Farsiu
Vahid Tarokh
DiffM
46
20
0
12 Jul 2020
Time Series Forecasting With Deep Learning: A Survey
Time Series Forecasting With Deep Learning: A Survey
Bryan Lim
S. Zohren
AI4TS
AI4CE
88
1,223
0
28 Apr 2020
Decision-Making with Auto-Encoding Variational Bayes
Decision-Making with Auto-Encoding Variational Bayes
Romain Lopez
Pierre Boyeau
Nir Yosef
Michael I. Jordan
Jeffrey Regier
BDL
393
10,591
0
17 Feb 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke
Sam Gross
Francisco Massa
Adam Lerer
James Bradbury
...
Sasank Chilamkurthy
Benoit Steiner
Lu Fang
Junjie Bai
Soumith Chintala
ODL
496
42,449
0
03 Dec 2019
A unified sparse optimization framework to learn parsimonious
  physics-informed models from data
A unified sparse optimization framework to learn parsimonious physics-informed models from data
Kathleen P. Champion
P. Zheng
Aleksandr Aravkin
Steven L. Brunton
J. Nathan Kutz
AI4CE
52
118
0
25 Jun 2019
An Introduction to Variational Autoencoders
An Introduction to Variational Autoencoders
Diederik P. Kingma
Max Welling
BDL
SSL
DRL
80
2,354
0
06 Jun 2019
Improved Conditional VRNNs for Video Prediction
Improved Conditional VRNNs for Video Prediction
Lluis Castrejon
Nicolas Ballas
Aaron Courville
VGen
DRL
126
163
0
27 Apr 2019
On the Convergence of Adam and Beyond
On the Convergence of Adam and Beyond
Sashank J. Reddi
Satyen Kale
Surinder Kumar
93
2,499
0
19 Apr 2019
Physics-Informed Generative Adversarial Networks for Stochastic
  Differential Equations
Physics-Informed Generative Adversarial Networks for Stochastic Differential Equations
Siyu Dai
Shawn Schaffert
Andreas G. Hofmann
120
365
0
05 Nov 2018
Quantifying total uncertainty in physics-informed neural networks for
  solving forward and inverse stochastic problems
Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems
Dongkun Zhang
Lu Lu
Ling Guo
George Karniadakis
UQCV
105
408
0
21 Sep 2018
A Unified Framework for Sparse Relaxed Regularized Regression: SR3
A Unified Framework for Sparse Relaxed Regularized Regression: SR3
P. Zheng
T. Askham
Steven L. Brunton
J. Nathan Kutz
Aleksandr Aravkin
40
139
0
14 Jul 2018
Sparse learning of stochastic dynamic equations
Sparse learning of stochastic dynamic equations
L. Boninsegna
Feliks Nuske
C. Clementi
42
217
0
06 Dec 2017
Learning Sparse Neural Networks through $L_0$ Regularization
Learning Sparse Neural Networks through L0L_0L0​ Regularization
Christos Louizos
Max Welling
Diederik P. Kingma
430
1,144
0
04 Dec 2017
Implicit Weight Uncertainty in Neural Networks
Implicit Weight Uncertainty in Neural Networks
Nick Pawlowski
Andrew Brock
Matthew C. H. Lee
Martin Rajchl
Ben Glocker
BDL
UQCV
118
94
0
03 Nov 2017
Categorical Reparameterization with Gumbel-Softmax
Categorical Reparameterization with Gumbel-Softmax
Eric Jang
S. Gu
Ben Poole
BDL
334
5,364
0
03 Nov 2016
The Concrete Distribution: A Continuous Relaxation of Discrete Random
  Variables
The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables
Chris J. Maddison
A. Mnih
Yee Whye Teh
BDL
193
2,533
0
02 Nov 2016
Variational Inference with Normalizing Flows
Variational Inference with Normalizing Flows
Danilo Jimenez Rezende
S. Mohamed
DRL
BDL
313
4,182
0
21 May 2015
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