PIED: Physics-Informed Experimental Design for Inverse Problems

10 March 2025

Papers citing "PIED: Physics-Informed Experimental Design for Inverse Problems"

27 / 27 papers shown

Title
Dipper: Diversity in Prompts for Producing Large Language Model Ensembles in Reasoning tasks Gregory Kang Ruey Lau Wenyang Hu Diwen Liu Jizhuo Chen Szu Hui Ng Bryan Kian Hsiang Low LRM AI4CE 122 8 0 12 Dec 2024
PINNACLE: PINN Adaptive ColLocation and Experimental points selection Gregory Kang Ruey Lau Apivich Hemachandra See-Kiong Ng K. H. Low 3DPC 116 20 0 11 Apr 2024
Batch Bayesian Optimization for Replicable Experimental Design Zhongxiang Dai Q. Nguyen Sebastian Shenghong Tay Daisuke Urano Richalynn Leong Bryan Kian Hsiang Low Patrick Jaillet 37 5 0 02 Nov 2023
Quantum Bayesian Optimization Zhongxiang Dai Gregory Kang Ruey Lau Arun Verma Yao Shu K. H. Low Patrick Jaillet 58 11 0 09 Oct 2023
Training-Free Neural Active Learning with Initialization-Robustness Guarantees Apivich Hemachandra Zhongxiang Dai Jasraj Singh See-Kiong Ng K. H. Low AAML 87 7 0 07 Jun 2023
Modern Bayesian Experimental Design Tom Rainforth Adam Foster Desi R. Ivanova Freddie Bickford-Smith 116 88 0 28 Feb 2023
Optimal design of large-scale nonlinear Bayesian inverse problems under model uncertainty A. Alexanderian R. Nicholson N. Petra 64 11 0 08 Nov 2022
A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks Chen-Chun Wu Min Zhu Qinyan Tan Yadhu Kartha Lu Lu 99 385 0 21 Jul 2022
Policy-Based Bayesian Experimental Design for Non-Differentiable Implicit Models Vincent Lim Ellen R. Novoseller Jeffrey Ichnowski Huang Huang Ken Goldberg OffRL 71 11 0 08 Mar 2022
Physics-informed neural networks for inverse problems in supersonic flows Ameya Dilip Jagtap Zhiping Mao Nikolaus Adams George Karniadakis PINN 51 225 0 23 Feb 2022
Implicit Deep Adaptive Design: Policy-Based Experimental Design without Likelihoods Desi R. Ivanova Adam Foster Steven Kleinegesse Michael U. Gutmann Tom Rainforth OffRL 129 48 0 03 Nov 2021
A novel meta-learning initialization method for physics-informed neural networks Xu Liu Xiaoya Zhang Wei Peng Weien Zhou Wen Yao AI4CE 73 76 0 23 Jul 2021
Efficient and Modular Implicit Differentiation Mathieu Blondel Quentin Berthet Marco Cuturi Roy Frostig Stephan Hoyer Felipe Llinares-López Fabian Pedregosa Jean-Philippe Vert 96 238 0 31 May 2021
Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design Adam Foster Desi R. Ivanova Ilyas Malik Tom Rainforth 69 85 0 03 Mar 2021
An Information-Theoretic Framework for Unifying Active Learning Problems Q. Nguyen Bryan Kian Hsiang Low Patrick Jaillet 53 18 0 19 Dec 2020
When and why PINNs fail to train: A neural tangent kernel perspective Sizhuang He Xinling Yu P. Perdikaris 141 928 0 28 Jul 2020
Physics-informed learning of governing equations from scarce data Zhao Chen Yang Liu Hao Sun PINN AI4CE 109 398 0 05 May 2020
EikoNet: Solving the Eikonal equation with Deep Neural Networks Jonathan D. Smith Kamyar Azizzadenesheli Zachary E. Ross 47 132 0 25 Mar 2020
Variational Bayesian Optimal Experimental Design Adam Foster M. Jankowiak Eli Bingham Paul Horsfall Yee Whye Teh Tom Rainforth Noah D. Goodman 99 140 0 13 Mar 2019
Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent Jaehoon Lee Lechao Xiao S. Schoenholz Yasaman Bahri Roman Novak Jascha Narain Sohl-Dickstein Jeffrey Pennington 218 1,111 0 18 Feb 2019
A Tutorial on Bayesian Optimization P. Frazier GP 118 1,799 0 08 Jul 2018
Neural Tangent Kernel: Convergence and Generalization in Neural Networks Arthur Jacot Franck Gabriel Clément Hongler 343 3,225 0 20 Jun 2018
On First-Order Meta-Learning Algorithms Alex Nichol Joshua Achiam John Schulman 256 2,239 0 08 Mar 2018
MINE: Mutual Information Neural Estimation Mohamed Ishmael Belghazi A. Baratin Sai Rajeswar Sherjil Ozair Yoshua Bengio Aaron Courville R. Devon Hjelm DRL 240 1,286 0 12 Jan 2018
Deep Neural Networks as Gaussian Processes Jaehoon Lee Yasaman Bahri Roman Novak S. Schoenholz Jeffrey Pennington Jascha Narain Sohl-Dickstein UQCV BDL 154 1,100 0 01 Nov 2017
Understanding Black-box Predictions via Influence Functions Pang Wei Koh Percy Liang TDI 232 2,913 0 14 Mar 2017
Fast Bayesian Optimal Experimental Design for Seismic Source Inversion Q. Long Mohammad Motamed Raúl Tempone 54 51 0 27 Feb 2015