Inference via low-dimensional couplings

17 March 2017

Youssef Marzouk

Papers citing "Inference via low-dimensional couplings"

50 / 62 papers shown

Title
A friendly introduction to triangular transport M. Ramgraber Daniel Sharp M. Le Provost Youssef Marzouk 63 0 0 27 Mar 2025
Learning local neighborhoods of non-Gaussian graphical models: A measure transport approach Sarah Liaw Rebecca E. Morrison Youssef Marzouk Ricardo Baptista 53 1 0 18 Mar 2025
Identification of Nonparametric Dynamic Causal Structure and Latent Process in Climate System Minghao Fu Zhen Zhang Zijian Li Yujia Zheng Ignavier Ng Yingyao Hu Anton van den Hengel CML 50 0 0 21 Jan 2025
Causal Order Discovery based on Monotonic SCMs Ali Izadi Martin Ester 31 0 0 24 Oct 2024
Weak neural variational inference for solving Bayesian inverse problems without forward models: applications in elastography Vincent C. Scholz Yaohua Zang P. Koutsourelakis 41 3 0 30 Jul 2024
Score matching through the roof: linear, nonlinear, and latent variables causal discovery Francesco Montagna P. M. Faller Patrick Bloebaum Elke Kirschbaum Francesco Locatello CML 87 0 0 26 Jul 2024
Variational Bayesian Optimal Experimental Design with Normalizing Flows Jiayuan Dong Christian L. Jacobsen Mehdi Khalloufi Maryam Akram Wanjiao Liu Karthik Duraisamy Xun Huan BDL 54 5 0 08 Apr 2024
Sequential transport maps using SoS density estimation and $α$ -divergences Benjamin Zanger Tiangang Cui Martin Schreiber O. Zahm 44 1 0 27 Feb 2024
Nonstationary Time Series Forecasting via Unknown Distribution Adaptation Zijian Li Ruichu Cai Zhenhui Yang Haiqin Huang Guan-Hong Chen Yifan Shen Zhengming Chen Xiangchen Song Kun Zhang OOD AI4TS 29 2 0 20 Feb 2024
Sampling in Unit Time with Kernel Fisher-Rao Flow A. Maurais Youssef Marzouk 26 12 0 08 Jan 2024
Distributed Nonlinear Filtering using Triangular Transport Maps Daniel Grange Ricardo Baptista Amirhossein Taghvaei Allen R. Tannenbaum Sean Phillips 27 1 0 29 Oct 2023
Temporally Disentangled Representation Learning under Unknown Nonstationarity Xiangchen Song Weiran Yao Yewen Fan Xinshuai Dong Guan-Hong Chen Juan Carlos Niebles Eric P. Xing Anton van den Hengel CML OOD 38 12 0 28 Oct 2023
An adaptive ensemble filter for heavy-tailed distributions: tuning-free inflation and localization M. Le Provost Ricardo Baptista J. Eldredge Youssef Marzouk 17 1 0 12 Oct 2023
Density Estimation via Measure Transport: Outlook for Applications in the Biological Sciences Vanessa López-Marrero Patrick R. Johnstone Gilchan Park Xihaier Luo OT 31 1 0 27 Sep 2023
A transport approach to sequential simulation-based inference Paul-Baptiste Rubio Youssef Marzouk M. Parno 35 1 0 26 Aug 2023
Learning Causal Graphs via Monotone Triangular Transport Maps S. Akbari Luca Ganassali Negar Kiyavash OT CML 16 8 0 26 May 2023
Generalized Precision Matrix for Scalable Estimation of Nonparametric Markov Networks Yujia Zheng Ignavier Ng Yewen Fan Anton van den Hengel 11 4 0 19 May 2023
Scalable Causal Discovery with Score Matching Francesco Montagna Nicoletta Noceti Lorenzo Rosasco Anton van den Hengel Francesco Locatello CML 52 25 0 06 Apr 2023
Self-reinforced polynomial approximation methods for concentrated probability densities Tiangang Cui S. Dolgov O. Zahm 24 5 0 05 Mar 2023
Progressive Bayesian Particle Flows based on Optimal Transport Map Sequences U. Hanebeck OT 16 1 0 04 Mar 2023
Dimension-reduced KRnet maps for high-dimensional Bayesian inverse problems Yani Feng Keju Tang Xiaoliang Wan Qifeng Liao 19 2 0 01 Mar 2023
An Approximation Theory Framework for Measure-Transport Sampling Algorithms Ricardo Baptista Bamdad Hosseini Nikola B. Kovachki Youssef M. Marzouk A. Sagiv OT 33 17 0 27 Feb 2023
Transport map unadjusted Langevin algorithms: learning and discretizing perturbed samplers Benjamin J. Zhang Youssef M. Marzouk K. Spiliopoulos 22 0 0 14 Feb 2023
Reduced-Order Autodifferentiable Ensemble Kalman Filters Yuming Chen D. Sanz-Alonso Rebecca Willett 39 8 0 27 Jan 2023
Tensor-train methods for sequential state and parameter learning in state-space models Yiran Zhao Tiangang Cui 24 2 0 24 Jan 2023
Ensemble transport smoothing. Part II: Nonlinear updates M. Ramgraber Ricardo Baptista D. McLaughlin Youssef Marzouk 23 6 0 31 Oct 2022
Ensemble transport smoothing. Part I: Unified framework M. Ramgraber Ricardo Baptista D. McLaughlin Youssef Marzouk 14 5 0 31 Oct 2022
Temporally Disentangled Representation Learning Weiran Yao Guangyi Chen Anton van den Hengel CML BDL OOD 32 48 0 24 Oct 2022
Deep importance sampling using tensor trains with application to a priori and a posteriori rare event estimation Tiangang Cui S. Dolgov Robert Scheichl 41 3 0 05 Sep 2022
On minimax density estimation via measure transport Sven Wang Youssef Marzouk OT 28 19 0 20 Jul 2022
Bayesian model calibration for block copolymer self-assembly: Likelihood-free inference and expected information gain computation via measure transport Ricardo Baptista Lianghao Cao Joshua Chen Omar Ghattas Fengyi Li Youssef M. Marzouk J. Oden 29 11 0 22 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 19 2 0 07 May 2022
Learning Latent Causal Dynamics Weiran Yao Guan-Hong Chen Anton van den Hengel OOD CML OffRL 19 13 0 10 Feb 2022
Heavy-tailed Sampling via Transformed Unadjusted Langevin Algorithm Ye He Krishnakumar Balasubramanian Murat A. Erdogdu 38 5 0 20 Jan 2022
Triangular Flows for Generative Modeling: Statistical Consistency, Smoothness Classes, and Fast Rates N. J. Irons M. Scetbon Soumik Pal Zaïd Harchaoui 33 17 0 31 Dec 2021
Scalable Bayesian transport maps for high-dimensional non-Gaussian spatial fields Matthias Katzfuss Florian Schafer OT 32 14 0 09 Aug 2021
Sparse approximation of triangular transports. Part II: the infinite dimensional case Jakob Zech Youssef Marzouk 20 19 0 28 Jul 2021
Augmented KRnet for density estimation and approximation Xiaoliang Wan Keju Tang 12 5 0 26 May 2021
Multiscale Invertible Generative Networks for High-Dimensional Bayesian Inference Shumao Zhang Pengchuan Zhang T. Hou BDL 9 4 0 12 May 2021
NF-iSAM: Incremental Smoothing and Mapping via Normalizing Flows Qiangqiang Huang Can Pu D. Fourie Kasra Khosoussi Jonathan P. How J. Leonard 23 12 0 11 May 2021
Learning non-Gaussian graphical models via Hessian scores and triangular transport Ricardo Baptista Youssef Marzouk Rebecca E. Morrison O. Zahm 31 23 0 08 Jan 2021
A unified performance analysis of likelihood-informed subspace methods Tiangang Cui X. Tong 21 26 0 07 Jan 2021
On the representation and learning of monotone triangular transport maps Ricardo Baptista Youssef Marzouk O. Zahm 11 46 0 22 Sep 2020
Deep composition of tensor-trains using squared inverse Rosenblatt transports Tiangang Cui S. Dolgov OT 26 33 0 14 Jul 2020
VAE-KRnet and its applications to variational Bayes Xiaoliang Wan Shuangqing Wei BDL DRL 11 13 0 29 Jun 2020
Scalable Approximate Inference and Some Applications Jun Han BDL 22 1 0 07 Mar 2020
Sequential Ensemble Transform for Bayesian Inverse Problems Aaron Myers Alexandre Hoang Thiery Kainan Wang T. Bui-Thanh 23 5 0 20 Sep 2019
MALA-within-Gibbs samplers for high-dimensional distributions with sparse conditional structure X. Tong M. Morzfeld Y. M. Marzouk 14 28 0 26 Aug 2019
Coupling techniques for nonlinear ensemble filtering Alessio Spantini Ricardo Baptista Youssef Marzouk 27 75 0 30 Jun 2019
Greedy inference with structure-exploiting lazy maps Michael C. Brennan Daniele Bigoni O. Zahm Alessio Spantini Youssef Marzouk 20 13 0 31 May 2019