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Efficient Prior Calibration From Indirect Data

28 May 2024

Papers citing "Efficient Prior Calibration From Indirect Data"

40 / 40 papers shown

Title
Stochastic Inverse Problem: stability, regularization and Wasserstein gradient flow Qin Li Maria Oprea Li Wang Yunan Yang 43 3 0 30 Sep 2024
A Primer on Variational Inference for Physics-Informed Deep Generative Modelling Alex Glyn-Davies Arnaud Vadeboncoeur O. Deniz Akyildiz Ieva Kazlauskaite Mark Girolami PINN 121 0 0 10 Sep 2024
BiLO: Bilevel Local Operator Learning for PDE inverse problems Ray Zirui Zhang Xiaohui Xie John S. Lowengrub 99 2 0 27 Apr 2024
Conditional Wasserstein Distances with Applications in Bayesian OT Flow Matching Jannis Chemseddine Paul Hagemann Gabriele Steidl Christian Wald 95 12 0 27 Mar 2024
Tweedie Moment Projected Diffusions For Inverse Problems Benjamin Boys Mark Girolami Jakiw Pidstrigach Sebastian Reich Alan Mosca O. Deniz Akyildiz MedIm 69 33 0 10 Oct 2023
Ambient Diffusion: Learning Clean Distributions from Corrupted Data Giannis Daras Kulin Shah Y. Dagan Aravind Gollakota A. Dimakis Adam R. Klivans DiffM 109 75 0 30 May 2023
Energy-Based Sliced Wasserstein Distance Khai Nguyen Nhat Ho 77 22 0 26 Apr 2023
Score-Based Diffusion Models as Principled Priors for Inverse Imaging Berthy Feng Jamie Smith Michael Rubinstein Huiwen Chang Katherine Bouman William T. Freeman DiffM 138 98 0 23 Apr 2023
Image Reconstruction without Explicit Priors Angela F. Gao Oscar Leong He Sun Katherine Bouman 62 8 0 21 Mar 2023
Random Grid Neural Processes for Parametric Partial Differential Equations Arnaud Vadeboncoeur Ieva Kazlauskaite Y. Papandreou F. Cirak Mark Girolami Ömer Deniz Akyildiz AI4CE 82 11 0 26 Jan 2023
Fully probabilistic deep models for forward and inverse problems in parametric PDEs Arnaud Vadeboncoeur Ömer Deniz Akyildiz Ieva Kazlauskaite Mark Girolami F. Cirak AI4CE 58 18 0 09 Aug 2022
Physics-Informed Neural Operator for Learning Partial Differential Equations Zong-Yi Li Hongkai Zheng Nikola B. Kovachki David Jin Haoxuan Chen Burigede Liu Kamyar Azizzadenesheli Anima Anandkumar AI4CE 121 424 0 06 Nov 2021
How to Train Your Energy-Based Models Yang Song Diederik P. Kingma DiffM 87 265 0 09 Jan 2021
Score-Based Generative Modeling through Stochastic Differential Equations Yang Song Jascha Narain Sohl-Dickstein Diederik P. Kingma Abhishek Kumar Stefano Ermon Ben Poole DiffM SyDa 370 6,586 0 26 Nov 2020
Fourier 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 509 2,453 0 18 Oct 2020
Denoising Diffusion Probabilistic Models Jonathan Ho Ajay Jain Pieter Abbeel DiffM 742 18,364 0 19 Jun 2020
A probabilistic generative model for semi-supervised training of coarse-grained surrogates and enforcing physical constraints through virtual observables Maximilian Rixner P. Koutsourelakis AI4CE 69 22 0 02 Jun 2020
Model Reduction and Neural Networks for Parametric PDEs K. Bhattacharya Bamdad Hosseini Nikola B. Kovachki Andrew M. Stuart 228 333 0 07 May 2020
Decision-Making with Auto-Encoding Variational Bayes Romain Lopez Pierre Boyeau Nir Yosef Michael I. Jordan Jeffrey Regier BDL 535 10,591 0 17 Feb 2020
Normalizing Flows for Probabilistic Modeling and Inference George Papamakarios Eric T. Nalisnick Danilo Jimenez Rezende S. Mohamed Balaji Lakshminarayanan TPM AI4CE 213 1,717 0 05 Dec 2019
Approximate Bayesian Computation with the Sliced-Wasserstein Distance Kimia Nadjahi Valentin De Bortoli Alain Durmus Roland Badeau Umut Simsekli 62 26 0 28 Oct 2019
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators Lu Lu Pengzhan Jin George Karniadakis 248 2,158 0 08 Oct 2019
Generative Modeling by Estimating Gradients of the Data Distribution Yang Song Stefano Ermon SyDa DiffM 258 3,961 0 12 Jul 2019
Invertible generative models for inverse problems: mitigating representation error and dataset bias Muhammad Asim Max Daniels Oscar Leong Ali Ahmed Paul Hand 164 154 0 28 May 2019
On the Convergence of Adam and Beyond Sashank J. Reddi Satyen Kale Surinder Kumar 109 2,506 0 19 Apr 2019
Max-Sliced Wasserstein Distance and its use for GANs Ishani Deshpande Yuan-Ting Hu Ruoyu Sun A. Pyrros Nasir Siddiqui Oluwasanmi Koyejo Zhizhen Zhao David A. Forsyth Alex Schwing GAN 56 201 0 11 Apr 2019
Physics-Constrained Deep Learning for High-dimensional Surrogate Modeling and Uncertainty Quantification without Labeled Data Yinhao Zhu N. Zabaras P. Koutsourelakis P. Perdikaris PINN AI4CE 115 871 0 18 Jan 2019
Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal Transport and Diffusions Antoine Liutkus Umut Simsekli Szymon Majewski Alain Durmus Fabian-Robert Stöter DiffM 98 122 0 21 Jun 2018
Learning to solve inverse problems using Wasserstein loss J. Adler Axel Ringh Ozan Oktem Johan Karlsson 58 38 0 30 Oct 2017
A Review on Bilevel Optimization: From Classical to Evolutionary Approaches and Applications Ankur Sinha P. Malo Kalyanmoy Deb 46 760 0 17 May 2017
A Consistent Bayesian Formulation for Stochastic Inverse Problems Based on Push-forward Measures T. Butler J. Jakeman T. Wildey 34 13 0 03 Apr 2017
Gaussian Error Linear Units (GELUs) Dan Hendrycks Kevin Gimpel 174 5,049 0 27 Jun 2016
An introduction to sampling via measure transport Youssef Marzouk Tarek A. El-Moselhy M. Parno Alessio Spantini OT 100 89 0 16 Feb 2016
Training generative neural networks via Maximum Mean Discrepancy optimization Gintare Karolina Dziugaite Daniel M. Roy Zoubin Ghahramani GAN 91 530 0 14 May 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.1K 150,364 0 22 Dec 2014
Well-Posed Bayesian Geometric Inverse Problems Arising in Subsurface Flow M. Iglesias Kui Lin Andrew M. Stuart 69 83 0 22 Jan 2014
Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances Marco Cuturi OT 220 4,294 0 04 Jun 2013
Equivalence of distance-based and RKHS-based statistics in hypothesis testing Dino Sejdinovic Bharath K. Sriperumbudur Arthur Gretton Kenji Fukumizu 232 688 0 25 Jul 2012
Bayesian Inference with Optimal Maps Tarek A. El-Moselhy Youssef M. Marzouk 120 290 0 07 Sep 2011
Uncertainty quantification and weak approximation of an elliptic inverse problem Masoumeh Dashti Andrew M. Stuart 73 102 0 01 Feb 2011