Bayesian Deep Convolutional Encoder-Decoder Networks for Surrogate Modeling and Uncertainty Quantification

21 January 2018

Papers citing "Bayesian Deep Convolutional Encoder-Decoder Networks for Surrogate Modeling and Uncertainty Quantification"

50 / 66 papers shown

Title
Transfer Learning on Multi-Dimensional Data: A Novel Approach to Neural Network-Based Surrogate Modeling Adrienne M. Propp Daniel M. Tartakovsky AI4CE 26 2 0 16 Oct 2024
PhyMPGN: Physics-encoded Message Passing Graph Network for spatiotemporal PDE systems Bocheng Zeng Qi Wang M. Yan Y. Liu Ruizhi Chengze Yi Zhang Hongsheng Liu Zidong Wang Hao Sun AI4CE 40 3 0 02 Oct 2024
Flexible SE(2) graph neural networks with applications to PDE surrogates Maria Bånkestad Olof Mogren Aleksis Pirinen 48 1 0 30 May 2024
Physics-Aware Neural Implicit Solvers for multiscale, parametric PDEs with applications in heterogeneous media Matthaios Chatzopoulos P. Koutsourelakis AI4CE 33 3 0 29 May 2024
Leveraging Interpolation Models and Error Bounds for Verifiable Scientific Machine Learning Tyler Chang Andrew Gillette R. Maulik 36 2 0 04 Apr 2024
Physics-Informed Diffusion Models Jan-Hendrik Bastek WaiChing Sun D. Kochmann DiffM AI4CE 47 10 0 21 Mar 2024
Approximation of Solution Operators for High-dimensional PDEs Nathan Gaby Xiaojing Ye 14 0 0 18 Jan 2024
Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference Philipp Reiser Javier Enrique Aguilar A. Guthke Paul-Christian Burkner 36 2 0 08 Dec 2023
Learning to simulate partially known spatio-temporal dynamics with trainable difference operators Xiang Huang Zhuoyuan Li Hongsheng Liu Zidong Wang Hongye Zhou Bin Dong Bei Hua AI4TS AI4CE 27 1 0 26 Jul 2023
Bi-fidelity Variational Auto-encoder for Uncertainty Quantification Nuojin Cheng Osman Asif Malik Subhayan De Stephen Becker Alireza Doostan 27 9 0 25 May 2023
In-Context Operator Learning with Data Prompts for Differential Equation Problems Liu Yang Siting Liu Tingwei Meng Stanley J. Osher 35 54 0 17 Apr 2023
$Laplace-fPINNs: Laplace-based fractional physics-informed neural networks for solving forward and inverse problems of subdiffusion$ Laplace-fPINNs: Laplace-based fractional physics-informed neural networks for solving forward and inverse problems of subdiffusion Xiongbin Yan Zhi-Qin John Xu Zheng Ma 29 2 0 03 Apr 2023
VI-DGP: A variational inference method with deep generative prior for solving high-dimensional inverse problems Yingzhi Xia Qifeng Liao Jinglai Li 19 2 0 22 Feb 2023
NeuralStagger: Accelerating Physics-constrained Neural PDE Solver with Spatial-temporal Decomposition Xinquan Huang Wenlei Shi Qi Meng Yue Wang Xiaotian Gao Jia Zhang Tie-Yan Liu AI4CE 21 8 0 20 Feb 2023
Multi-Scale Message Passing Neural PDE Solvers Léonard Equer T. Konstantin Rusch Siddhartha Mishra AI4CE 22 12 0 07 Feb 2023
Algorithmically Designed Artificial Neural Networks (ADANNs): Higher order deep operator learning for parametric partial differential equations Arnulf Jentzen Adrian Riekert Philippe von Wurstemberger 21 1 0 07 Feb 2023
Sampling-Based Accuracy Testing of Posterior Estimators for General Inference Pablo Lemos A. Coogan Y. Hezaveh Laurence Perreault Levasseur 34 30 0 06 Feb 2023
An Enhanced V-cycle MgNet Model for Operator Learning in Numerical Partial Differential Equations Jianqing Zhu Juncai He Qiumei Huang 30 4 0 02 Feb 2023
KoopmanLab: machine learning for solving complex physics equations Wei Xiong Muyuan Ma Xiaomeng Huang Ziyang Zhang Pei Sun Yang Tian AI4CE 26 13 0 03 Jan 2023
An Introduction to Kernel and Operator Learning Methods for Homogenization by Self-consistent Clustering Analysis Owen Huang Sourav Saha Jiachen Guo Wing Kam Liu AI4CE 8 12 0 01 Dec 2022
Bayesian Inversion with Neural Operator (BINO) for Modeling Subdiffusion: Forward and Inverse Problems Xiongbin Yan Z. Xu Zheng Ma 8 2 0 22 Nov 2022
Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks in Scientific Computing Salah A. Faroughi N. Pawar C. Fernandes Maziar Raissi Subasish Das N. Kalantari S. K. Mahjour PINN AI4CE 27 48 0 14 Nov 2022
Learning Relaxation for Multigrid Dmitry Kuznichov AI4CE 13 1 0 25 Jul 2022
Fourier Neural Operator with Learned Deformations for PDEs on General Geometries Zong-Yi Li Daniel Zhengyu Huang Burigede Liu Anima Anandkumar AI4CE 113 249 0 11 Jul 2022
Uncertainty quantification of two-phase flow in porous media via coupled-TgNN surrogate model Jun Yu Li Dongxiao Zhang Tianhao He Q. Zheng AI4CE 22 6 0 28 May 2022
Transformer for Partial Differential Equations' Operator Learning Zijie Li Kazem Meidani A. Farimani 42 140 0 26 May 2022
Multifidelity data fusion in convolutional encoder/decoder networks Lauren Partin Gianluca Geraci A. Rushdi M. Eldred Daniele E. Schiavazzi UQCV AI4CE 27 13 0 10 May 2022
Use of Multifidelity Training Data and Transfer Learning for Efficient Construction of Subsurface Flow Surrogate Models Su Jiang L. Durlofsky AI4CE 22 29 0 23 Apr 2022
Deep reinforcement learning for optimal well control in subsurface systems with uncertain geology Y. Nasir L. Durlofsky OffRL AI4CE 19 16 0 24 Mar 2022
Physics Informed RNN-DCT Networks for Time-Dependent Partial Differential Equations Benwei Wu O. Hennigh Jan Kautz S. Choudhry Wonmin Byeon MLAU AI4CE 4 10 0 24 Feb 2022
A Bayesian Deep Learning Approach to Near-Term Climate Prediction Xihaier Luo B. Nadiga Yihui Ren Ji Hwan Park Wei Xu Shinjae Yoo BDL AI4CE 14 10 0 23 Feb 2022
Stochastic Modeling of Inhomogeneities in the Aortic Wall and Uncertainty Quantification using a Bayesian Encoder-Decoder Surrogate Sascha Ranftl Malte Rolf-Pissarczyk G. Wolkerstorfer Antonio Pepe Jan Egger W. Linden G. Holzapfel 23 9 0 21 Feb 2022
Physics-informed neural networks for solving parametric magnetostatic problems Andrés Beltrán-Pulido Ilias Bilionis D. Aliprantis 24 34 0 08 Feb 2022
A heteroencoder architecture for prediction of failure locations in porous metals using variational inference Wyatt Bridgman Xiaoxuan Zhang G. Teichert M. Khalil K. Garikipati Reese E. Jones UQCV AI4CE 13 5 0 31 Jan 2022
Discovering Nonlinear PDEs from Scarce Data with Physics-encoded Learning Chengping Rao Pu Ren Yang Liu Hao-Lun Sun AI4CE 43 26 0 28 Jan 2022
Deep Nonparametric Estimation of Operators between Infinite Dimensional Spaces Hao Liu Haizhao Yang Minshuo Chen T. Zhao Wenjing Liao 32 36 0 01 Jan 2022
DeepParticle: learning invariant measure by a deep neural network minimizing Wasserstein distance on data generated from an interacting particle method Zhongjian Wang Jack Xin Zhiwen Zhang 39 15 0 02 Nov 2021
slimTrain -- A Stochastic Approximation Method for Training Separable Deep Neural Networks Elizabeth Newman Julianne Chung Matthias Chung Lars Ruthotto 39 6 0 28 Sep 2021
Wasserstein Generative Adversarial Uncertainty Quantification in Physics-Informed Neural Networks Yihang Gao Michael K. Ng 27 28 0 30 Aug 2021
Learning Partial Differential Equations in Reproducing Kernel Hilbert Spaces George Stepaniants 43 15 0 26 Aug 2021
Choose a Transformer: Fourier or Galerkin Shuhao Cao 39 220 0 31 May 2021
Stein's Method Meets Computational Statistics: A Review of Some Recent Developments Andreas Anastasiou Alessandro Barp F. Briol B. Ebner Robert E. Gaunt ... Qiang Liu Lester W. Mackey Chris J. Oates G. Reinert Yvik Swan 22 35 0 07 May 2021
A Deep Learning approach to Reduced Order Modelling of Parameter Dependent Partial Differential Equations N. R. Franco Andrea Manzoni P. Zunino 18 45 0 10 Mar 2021
Teaching the Incompressible Navier-Stokes Equations to Fast Neural Surrogate Models in 3D Nils Wandel Michael Weinmann Reinhard Klein AI4CE 26 50 0 22 Dec 2020
Beyond Point Estimate: Inferring Ensemble Prediction Variation from Neuron Activation Strength in Recommender Systems Zhe Chen Yuyan Wang Dong Lin D. Cheng Lichan Hong Ed H. Chi Claire Cui 28 16 0 17 Aug 2020
Multipole Graph Neural Operator for Parametric Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 15 371 0 16 Jun 2020
Physics informed deep learning for computational elastodynamics without labeled data Chengping Rao Hao-Lun Sun Yang Liu PINN AI4CE 15 222 0 10 Jun 2020
Multi-fidelity Generative Deep Learning Turbulent Flows N. Geneva N. Zabaras AI4CE 16 44 0 08 Jun 2020
Transfer learning based multi-fidelity physics informed deep neural network S. Chakraborty PINN OOD AI4CE 7 163 0 19 May 2020
CAZSL: Zero-Shot Regression for Pushing Models by Generalizing Through Context Wenyu Zhang Skyler Seto Devesh K. Jha 18 5 0 26 Mar 2020