Conditional deep surrogate models for stochastic, high-dimensional, and multi-fidelity systems

15 January 2019

Papers citing "Conditional deep surrogate models for stochastic, high-dimensional, and multi-fidelity systems"

20 / 20 papers shown

Title
PINNs for Medical Image Analysis: A Survey C. Banerjee Kien Nguyen Olivier Salvado Truyen Tran Clinton Fookes AI4CE 29 1 0 02 Aug 2024
Physics-Aware Neural Implicit Solvers for multiscale, parametric PDEs with applications in heterogeneous media Matthaios Chatzopoulos P. Koutsourelakis AI4CE 29 3 0 29 May 2024
Dimensionality reduction can be used as a surrogate model for high-dimensional forward uncertainty quantification Jungho Kim Sang-ri Yi Ziqi Wang 19 5 0 07 Feb 2024
A Survey on Physics Informed Reinforcement Learning: Review and Open Problems C. Banerjee Kien Nguyen Clinton Fookes M. Raissi PINN AI4CE 16 5 0 05 Sep 2023
Physics-Informed Computer Vision: A Review and Perspectives C. Banerjee Kien Nguyen Clinton Fookes G. Karniadakis PINN AI4CE 30 27 0 29 May 2023
PastNet: Introducing Physical Inductive Biases for Spatio-temporal Video Prediction Hao Wu Wei Xion Fan Xu Xian-Sheng Hua C. L. Philip Chen Xiansheng Hua AI4TS 14 27 0 19 May 2023
Conditional deep generative models as surrogates for spatial field solution reconstruction with quantified uncertainty in Structural Health Monitoring applications Nicholas E. Silionis Theodora Liangou K. Anyfantis AI4CE 16 0 0 14 Feb 2023
Random Grid Neural Processes for Parametric Partial Differential Equations A. Vadeboncoeur Ieva Kazlauskaite Y. Papandreou F. Cirak Mark Girolami Ömer Deniz Akyildiz AI4CE 20 11 0 26 Jan 2023
Fully probabilistic deep models for forward and inverse problems in parametric PDEs A. Vadeboncoeur Ömer Deniz Akyildiz Ieva Kazlauskaite Mark Girolami F. Cirak AI4CE 20 17 0 09 Aug 2022
PARC: Physics-Aware Recurrent Convolutional Neural Networks to Assimilate Meso-scale Reactive Mechanics of Energetic Materials Phong C. H. Nguyen Y. Nguyen Joseph B. Choi P. Seshadri H. Udaykumar Stephen Seung-Yeob Baek AI4CE 16 16 0 04 Apr 2022
Deep Capsule Encoder-Decoder Network for Surrogate Modeling and Uncertainty Quantification A. Thakur S. Chakraborty MedIm 28 4 0 19 Jan 2022
Prediction of liquid fuel properties using machine learning models with Gaussian processes and probabilistic conditional generative learning Rodolfo S. M. Freitas Ágatha P. F. Lima Cheng Chen F. Rochinha D. Mira Xi Jiang 15 0 0 18 Oct 2021
A Physics Informed Neural Network Approach to Solution and Identification of Biharmonic Equations of Elasticity M. Vahab E. Haghighat M. Khaleghi N. Khalili PINN 29 43 0 16 Aug 2021
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges Cynthia Rudin Chaofan Chen Zhi Chen Haiyang Huang Lesia Semenova Chudi Zhong FaML AI4CE LRM 43 650 0 20 Mar 2021
A Genetic Algorithm with Tree-structured Mutation for Hyperparameter Optimisation of Graph Neural Networks Yingfang Yuan Wenjun Wang Wei Pang 18 9 0 24 Feb 2021
A probabilistic generative model for semi-supervised training of coarse-grained surrogates and enforcing physical constraints through virtual observables Maximilian Rixner P. Koutsourelakis AI4CE 11 17 0 02 Jun 2020
Bayesian differential programming for robust systems identification under uncertainty Yibo Yang Mohamed Aziz Bhouri P. Perdikaris OOD 25 32 0 15 Apr 2020
Incorporating physical constraints in a deep probabilistic machine learning framework for coarse-graining dynamical systems Sebastian Kaltenbach P. Koutsourelakis AI4CE 14 34 0 30 Dec 2019
A physics-aware, probabilistic machine learning framework for coarse-graining high-dimensional systems in the Small Data regime Constantin Grigo P. Koutsourelakis AI4CE 13 25 0 11 Feb 2019
A deep generative model for gene expression profiles from single-cell RNA sequencing Romain Lopez Jeffrey Regier Michael Cole Michael I. Jordan N. Yosef BDL 16 7 0 07 Sep 2017