Geometric MCMC for Infinite-Dimensional Inverse Problems

20 June 2016

Papers citing "Geometric MCMC for Infinite-Dimensional Inverse Problems"

50 / 70 papers shown

Title
Non-parametric Inference for Diffusion Processes: A Computational Approach via Bayesian Inversion for PDEs Maximilian Kruse Sebastian Krumscheid 26 0 0 04 Nov 2024
Sacred and Profane: from the Involutive Theory of MCMC to Helpful Hamiltonian Hacks N. Glatt-Holtz Andrew J. Holbrook J. Krometis Cecilia F. Mondaini Ami D. Sheth 28 0 0 22 Oct 2024
Valid Credible Ellipsoids for Linear Functionals by a Renormalized Bernstein-von Mises Theorem Gustav Rømer 19 0 0 17 Sep 2024
Taming Score-Based Diffusion Priors for Infinite-Dimensional Nonlinear Inverse Problems Lorenzo Baldassari Ali Siahkoohi Josselin Garnier K. Sølna Maarten V. de Hoop DiffM 31 1 0 24 May 2024
Gaussian Measures Conditioned on Nonlinear Observations: Consistency, MAP Estimators, and Simulation Yifan Chen Bamdad Hosseini H. Owhadi Andrew M. Stuart 51 1 0 21 May 2024
Statistical algorithms for low-frequency diffusion data: A PDE approach Matteo Giordano Sven Wang 33 2 0 02 May 2024
Bayesian Nonparametric Inference in McKean-Vlasov models Richard Nickl G. Pavliotis Kolyan Ray 21 5 0 25 Apr 2024
Diffeomorphic Measure Matching with Kernels for Generative Modeling Biraj Pandey Bamdad Hosseini Pau Batlle H. Owhadi 20 3 0 12 Feb 2024
SMC Is All You Need: Parallel Strong Scaling Xin Liang J. Lukens Sanjaya Lohani Brian T. Kirby T. Searles Kody J. H. Law 20 2 0 09 Feb 2024
Deep Gaussian Process Priors for Bayesian Inference in Nonlinear Inverse Problems Kweku Abraham Neil Deo 20 4 0 21 Dec 2023
Scaling Up Bayesian Neural Networks with Neural Networks Zahra Moslemi Yang Meng Shiwei Lan B. Shahbaba BDL 22 1 0 19 Dec 2023
Conditional Optimal Transport on Function Spaces Bamdad Hosseini Alexander W. Hsu Amirhossein Taghvaei OT 34 14 0 09 Nov 2023
A Risk Management Perspective on Statistical Estimation and Generalized Variational Inference Aurya Javeed D. Kouri T. Surowiec 15 2 0 26 Oct 2023
On posterior consistency of data assimilation with Gaussian process priors: the 2D Navier-Stokes equations Richard Nickl E. Titi 11 7 0 16 Jul 2023
Spatiotemporal Besov Priors for Bayesian Inverse Problems Shiwei Lan M. Pasha Shuyi Li Weining Shen 16 5 0 28 Jun 2023
Principal Feature Detection via $Φ$ -Sobolev Inequalities Matthew T.C. Li Youssef Marzouk O. Zahm 24 8 0 10 May 2023
Reversibility of elliptical slice sampling revisited Mareike Hasenpflug Viacheslav Natarovskii Daniel Rudolf 19 5 0 06 Jan 2023
Consistent inference for diffusions from low frequency measurements Richard Nickl 27 5 0 24 Oct 2022
Bayesian Learning via Q-Exponential Process Shuyi Li Michael O'Connor Shiwei Lan 21 2 0 14 Oct 2022
Adaptive inference over Besov spaces in the white noise model using $p$ -exponential priors S. Agapiou Aimilia Savva 13 2 0 13 Sep 2022
Semi-supervised Invertible Neural Operators for Bayesian Inverse Problems Sebastian Kaltenbach P. Perdikaris P. Koutsourelakis 10 23 0 06 Sep 2022
On free energy barriers in Gaussian priors and failure of cold start MCMC for high-dimensional unimodal distributions Afonso S. Bandeira Antoine Maillard Richard Nickl Sven Wang 12 8 0 05 Sep 2022
Chilled Sampling for Uncertainty Quantification: A Motivation From A Meteorological Inverse Problem P. Héas Frédéric Cérou Mathias Rousset 9 3 0 07 Jul 2022
Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative Learning Thomas O'Leary-Roseberry Peng Chen Umberto Villa Omar Ghattas AI4CE 26 39 0 21 Jun 2022
Variational Inference for Nonlinear Inverse Problems via Neural Net Kernels: Comparison to Bayesian Neural Networks, Application to Topology Optimization Vahid Keshavarzzadeh Robert M. Kirby A. Narayan BDL 16 2 0 07 May 2022
A gradient-free subspace-adjusting ensemble sampler for infinite-dimensional Bayesian inverse problems Matthew M. Dunlop G. Stadler BDL 8 6 0 22 Feb 2022
Multilevel Delayed Acceptance MCMC Mikkel B. Lykkegaard T. Dodwell C. Fox Grigorios Mingas Robert Scheichl 16 14 0 08 Feb 2022
Lagrangian Manifold Monte Carlo on Monge Patches M. Hartmann Mark Girolami Arto Klami 16 10 0 01 Feb 2022
Dimension-independent Markov chain Monte Carlo on the sphere H. Lie Daniel Rudolf Björn Sprungk T. Sullivan 19 6 0 22 Dec 2021
Bayesian neural network priors for edge-preserving inversion Chen Li Matthew M. Dunlop G. Stadler 13 12 0 20 Dec 2021
Laplace priors and spatial inhomogeneity in Bayesian inverse problems S. Agapiou Sven Wang 15 13 0 10 Dec 2021
hIPPYlib-MUQ: A Bayesian Inference Software Framework for Integration of Data with Complex Predictive Models under Uncertainty Ki-tae Kim Umberto Villa M. Parno Youssef Marzouk Omar Ghattas N. Petra 17 18 0 01 Dec 2021
Variational Bayesian Approximation of Inverse Problems using Sparse Precision Matrices Jan Povala Ieva Kazlauskaite Eky Febrianto F. Cirak Mark Girolami 26 22 0 22 Oct 2021
Statistical Finite Elements via Langevin Dynamics Ömer Deniz Akyildiz Connor Duffin Sotirios Sabanis Mark Girolami 23 11 0 21 Oct 2021
Consistency of Bayesian inference with Gaussian process priors for a parabolic inverse problem Hanne Kekkonen 11 11 0 24 Mar 2021
Data-Free Likelihood-Informed Dimension Reduction of Bayesian Inverse Problems Tiangang Cui O. Zahm 15 22 0 26 Feb 2021
Projected Wasserstein gradient descent for high-dimensional Bayesian inference Yifei Wang Peng Chen Wuchen Li 11 25 0 12 Feb 2021
Novel Deep neural networks for solving Bayesian statistical inverse Harbir Antil H. Elman Akwum Onwunta Deepanshu Verma BDL 16 17 0 08 Feb 2021
Scaling Up Bayesian Uncertainty Quantification for Inverse Problems using Deep Neural Networks Shiwei Lan Shuyi Li B. Shahbaba UQCV BDL 17 16 0 11 Jan 2021
A unified performance analysis of likelihood-informed subspace methods Tiangang Cui X. Tong 17 26 0 07 Jan 2021
Trace-class Gaussian priors for Bayesian learning of neural networks with MCMC Torben Sell Sumeetpal S. Singh BDL 15 5 0 20 Dec 2020
On the accept-reject mechanism for Metropolis-Hastings algorithms N. Glatt-Holtz J. Krometis Cecilia F. Mondaini 20 10 0 09 Nov 2020
Ensemble sampler for infinite-dimensional inverse problems Jeremie Coullon R. Webber 11 10 0 28 Oct 2020
Statistical guarantees for Bayesian uncertainty quantification in non-linear inverse problems with Gaussian process priors F. Monard Richard Nickl G. Paternain 17 35 0 31 Jul 2020
Multilevel Hierarchical Decomposition of Finite Element White Noise with Application to Multilevel Markov Chain Monte Carlo Hillary R. Fairbanks U. Villa P. Vassilevski 21 7 0 28 Jul 2020
Non-Stationary Multi-layered Gaussian Priors for Bayesian Inversion M. Emzir Sari Lasanen Z. Purisha L. Roininen Simo Särkkä 16 9 0 28 Jun 2020
Multimodal Bayesian Registration of Noisy Functions using Hamiltonian Monte Carlo J. D. Tucker L. Shand K. Chowdhary 13 7 0 29 May 2020
Stability of Gibbs Posteriors from the Wasserstein Loss for Bayesian Full Waveform Inversion Matthew M. Dunlop Yunan Yang 17 12 0 07 Apr 2020
Mixing Rates for Hamiltonian Monte Carlo Algorithms in Finite and Infinite Dimensions N. Glatt-Holtz Cecilia F. Mondaini 21 10 0 17 Mar 2020
Generalized Parallel Tempering on Bayesian Inverse Problems J. Latz Juan P. Madrigal-Cianci F. Nobile Raúl Tempone 11 16 0 06 Mar 2020