The Normal Law Under Linear Restrictions: Simulation and Estimation via Minimax Tilting

14 March 2016

Papers citing "The Normal Law Under Linear Restrictions: Simulation and Estimation via Minimax Tilting"

50 / 51 papers shown

Title
Mixing times of data-augmentation Gibbs samplers for high-dimensional probit regression Filippo Ascolani Giacomo Zanella 119 0 0 20 May 2025
Exact MCMC for Intractable Proposals Dwija Kakkad Dootika Vats 68 0 0 14 Oct 2024
Analysing symbolic data by pseudo-marginal methods Yu Yang M. Quiroz B. Beranger Robert Kohn Scott A. Sisson 55 0 0 08 Aug 2024
Scalable expectation propagation for generalized linear models Niccolò Anceschi A. Fasano Beatrice Franzolini Giovanni Rebaudo 91 0 0 02 Jul 2024
Scalable Sampling of Truncated Multivariate Normals Using Sequential Nearest-Neighbor Approximation Jian Cao Matthias Katzfuss 56 0 0 25 Jun 2024
Parallel Approximations for High-Dimensional Multivariate Normal Probability Computation in Confidence Region Detection Applications Xiran Zhang Sameh Abdulah JIAN-PENG Cao Hatem Ltaief Ying Sun M. Genton David E. Keyes 40 1 0 18 May 2024
Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning Jörn Tebbe Christoph Zimmer A. Steland Markus Lange-Hegermann Fabian Mies GP 92 3 0 28 Feb 2024
Spectral gap bounds for reversible hybrid Gibbs chains Qian Qin Nianqiao Ju Guanyang Wang 83 5 0 20 Dec 2023
Linear-Cost Vecchia Approximation of Multivariate Normal Probabilities Jian Cao Matthias Katzfuss 71 1 0 15 Nov 2023
An Easy Rejection Sampling Baseline via Gradient Refined Proposals Edward Raff Mark McLean James Holt 57 0 0 30 Sep 2023
Expectation propagation for the smoothing distribution in dynamic probit Niccolò Anceschi A. Fasano Giovanni Rebaudo 62 0 0 04 Sep 2023
Characterizing Data Point Vulnerability via Average-Case Robustness Tessa Han Suraj Srinivas Himabindu Lakkaraju AAML OOD 112 1 0 26 Jul 2023
Density Ratio Estimation-based Bayesian Optimization with Semi-Supervised Learning Jungtaek Kim 86 1 0 24 May 2023
Utility Theory of Synthetic Data Generation Shi Xu W. Sun Guang Cheng 174 5 0 17 May 2023
SOBER: Highly Parallel Bayesian Optimization and Bayesian Quadrature over Discrete and Mixed Spaces Masaki Adachi Satoshi Hayakawa Saad Hamid Martin Jørgensen Harald Oberhauser Michael A. Osborne 88 7 0 27 Jan 2023
hdtg: An R package for high-dimensional truncated normal simulation Zhenyu Zhang A. Chin A. Nishimura M. Suchard 37 4 0 23 Sep 2022
An extension of the Unified Skew-Normal family of distributions and application to Bayesian binary regression P. Onorati B. Liseo 84 3 0 07 Sep 2022
A Parallel Technique for Multi-objective Bayesian Global Optimization: Using a Batch Selection of Probability of Improvement Kaifeng Yang Guozhi Dong M. Affenzeller 69 7 0 07 Aug 2022
On Controller Tuning with Time-Varying Bayesian Optimization Paul Brunzema Alexander von Rohr Sebastian Trimpe 79 17 0 22 Jul 2022
Bayesian Optimization Over Iterative Learners with Structured Responses: A Budget-aware Planning Approach Syrine Belakaria J. Doppa Nicolò Fusi Rishit Sheth 106 7 0 25 Jun 2022
Bayesian conjugacy in probit, tobit, multinomial probit and extensions: A review and new results Niccolò Anceschi A. Fasano Daniele Durante Giacomo Zanella 85 18 0 16 Jun 2022
Semi-Parametric Contextual Bandits with Graph-Laplacian Regularization Y. Choi Gi-Soo Kim Seung-Jin Paik M. Paik 64 6 0 17 May 2022
Efficient CDF Approximations for Normalizing Flows Chandramouli Shama Sastry Andreas M. Lehrmann Marcus A. Brubaker A. Radovic 28 1 0 23 Feb 2022
Warped Dynamic Linear Models for Time Series of Counts Brian King Daniel R. Kowal AI4TS 126 5 0 27 Oct 2021
Approximation Methods for Mixed Models with Probit Link Functions Benjamin Christoffersen Mark Clements Hedvig Kjellström K. Humphreys 20 0 0 27 Oct 2021
Semiparametric discrete data regression with Monte Carlo inference and prediction Daniel R. Kowal Bo-Hong Wu 126 3 0 23 Oct 2021
Bayesian inference on high-dimensional multivariate binary responses Antik Chakraborty Rihui Ou David B. Dunson 36 4 0 03 Jun 2021
Variational Inference for the Smoothing Distribution in Dynamic Probit Models A. Fasano Giovanni Rebaudo 55 4 0 15 Apr 2021
A Hybrid Approximation to the Marginal Likelihood Eric Chuu D. Pati A. Bhattacharya 44 2 0 24 Feb 2021
Asymptotically Exact and Fast Gaussian Copula Models for Imputation of Mixed Data Types Benjamin Christoffersen M. Clements K. Humphreys Hedvig Kjellström 70 3 0 04 Feb 2021
A unified framework for closed-form nonparametric regression, classification, preference and mixed problems with Skew Gaussian Processes A. Benavoli Dario Azzimonti Dario Piga 67 15 0 12 Dec 2020
Scalable computation of predictive probabilities in probit models with Gaussian process priors JIAN-PENG Cao Daniele Durante M. Genton 91 11 0 03 Sep 2020
A Class of Conjugate Priors for Multinomial Probit Models which Includes the Multivariate Normal One A. Fasano Daniele Durante 80 27 0 14 Jul 2020
A Survey of Constrained Gaussian Process Regression: Approaches and Implementation Challenges L. Swiler Mamikon A. Gulian A. Frankel Cosmin Safta J. Jakeman GP AI4CE 110 107 0 16 Jun 2020
Skew Gaussian Processes for Classification A. Benavoli Dario Azzimonti Dario Piga GP 63 19 0 26 May 2020
Interpretable Safety Validation for Autonomous Vehicles Anthony Corso Mykel J. Kochenderfer 75 24 0 14 Apr 2020
Exploiting Low Rank Covariance Structures for Computing High-Dimensional Normal and Student- $t$ Probabilities JIAN-PENG Cao M. Genton David E. Keyes G. Turkiyyah 66 13 0 25 Mar 2020
Scalable and Accurate Variational Bayes for High-Dimensional Binary Regression Models A. Fasano Daniele Durante Giacomo Zanella 99 32 0 15 Nov 2019
Integrals over Gaussians under Linear Domain Constraints A. Gessner Oindrila Kanjilal Philipp Hennig 69 30 0 21 Oct 2019
An Efficient Sampling Algorithm for Non-smooth Composite Potentials Wenlong Mou Nicolas Flammarion Martin J. Wainwright Peter L. Bartlett 66 24 0 01 Oct 2019
Fast and Exact Simulation of Multivariate Normal and Wishart Random Variables with Box Constraints Hillary Koch Gregory P. Bopp 55 3 0 28 Jun 2019
Gaussian Process Modulated Cox Processes under Linear Inequality Constraints A. F. López-Lopera S. T. John N. Durrande 85 16 0 28 Feb 2019
Approximating Gaussian Process Emulators with Linear Inequality Constraints and Noisy Observations via MC and MCMC A. F. López-Lopera François Bachoc N. Durrande Jérémy Rohmer Déborah Idier O. Roustant 35 12 0 15 Jan 2019
Gaussian processes with linear operator inequality constraints C. Agrell 83 39 0 10 Jan 2019
The Soft Multivariate Truncated Normal Distribution with Applications to Bayesian Constrained Estimation Allyson Souris A. Bhattacharya D. Pati 20 3 0 24 Jul 2018
Bayesian Metabolic Flux Analysis reveals intracellular flux couplings Markus Heinonen Maria Osmala Henrik Mannerstrom J. Wallenius Samuel Kaski Juho Rousu Harri Lähdesmäki 43 22 0 18 Apr 2018
Conjugate Bayes for probit regression via unified skew-normal distributions Daniele Durante 84 58 0 26 Feb 2018
Finite-dimensional Gaussian approximation with linear inequality constraints A. F. López-Lopera François Bachoc N. Durrande O. Roustant 140 67 0 20 Oct 2017
Bayesian Optimization with Shape Constraints Michael Jauch Víctor Pena 47 11 0 28 Dec 2016
Flexible Bayesian Quantile Regression in Ordinal Models M. A. Rahman Shubham Karnawat 100 15 0 02 Sep 2016