Expectation Propagation for approximate Bayesian inference

10 January 2013

Papers citing "Expectation Propagation for approximate Bayesian inference"

50 / 491 papers shown

Title
Functional Tensors for Probabilistic Programming F. Obermeyer Eli Bingham M. Jankowiak Du Phan Jonathan P. Chen 9 17 0 23 Oct 2019
Optimistic Distributionally Robust Optimization for Nonparametric Likelihood Approximation Viet Anh Nguyen Soroosh Shafieezadeh-Abadeh Man-Chung Yue Daniel Kuhn W. Wiesemann 6 29 0 23 Oct 2019
Constrained Bayesian Optimization with Max-Value Entropy Search Valerio Perrone I. Shcherbatyi Rodolphe Jenatton Cédric Archambeau Matthias Seeger 13 41 0 15 Oct 2019
Probabilistic Time of Arrival Localization Fernando Perez-Cruz Pablo Martínez Olmos M. Zhang Howard Huang 9 9 0 15 Oct 2019
Stochastic triangular mesh mapping: A terrain mapping technique for autonomous mobile robots C. Dufauret Lombard C. E. V. Daalen 3DV 22 5 0 08 Oct 2019
The $f$ -Divergence Expectation Iteration Scheme Kamélia Daudel Randal Douc Franccois Portier François Roueff 17 1 0 26 Sep 2019
A Theory of Uncertainty Variables for State Estimation and Inference Rajat Talak S. Karaman E. Modiano 11 1 0 24 Sep 2019
Knowledge representation and diagnostic inference using Bayesian networks in the medical discourse Sebastian Flügge Sandra Zimmer U. Petersohn 14 5 0 18 Sep 2019
Adversarial $α$ -divergence Minimization for Bayesian Approximate Inference Simón Rodríguez Santana Daniel Hernández-Lobato UQCV BDL 12 7 0 13 Sep 2019
Correcting Predictions for Approximate Bayesian Inference Tomasz Kuśmierczyk J. Sakaya Arto Klami 11 10 0 11 Sep 2019
$α$ Belief Propagation as Fully Factorized Approximation Dong Liu N. N. Moghadam L. Rasmussen Jinliang Huang S. Chatterjee 8 3 0 23 Aug 2019
Convergence Rates of Variational Inference in Sparse Deep Learning Badr-Eddine Chérief-Abdellatif BDL 14 38 0 09 Aug 2019
Probabilistic Models with Deep Neural Networks A. Masegosa Rafael Cabañas H. Langseth Thomas D. Nielsen Antonio Salmerón BDL 6 12 0 09 Aug 2019
Probabilistic Residual Learning for Aleatoric Uncertainty in Image Restoration Chen Zhang Bangti Jin UQCV 22 12 0 01 Aug 2019
Classified Regression for Bayesian Optimization: Robot Learning with Unknown Penalties A. Marco Dominik Baumann Philipp Hennig Sebastian Trimpe 9 3 0 24 Jul 2019
Accelerating Experimental Design by Incorporating Experimenter Hunches Cheng Li Santu Rana Sunil R. Gupta Vu Nguyen Svetha Venkatesh ... David Rubín de Celis Leal Teo Slezak Murray Height M. Mohammed I. Gibson 22 33 0 22 Jul 2019
Stochastic gradient Markov chain Monte Carlo Christopher Nemeth Paul Fearnhead BDL 22 134 0 16 Jul 2019
Understanding Phase Transitions via Mutual Information and MMSE Galen Reeves H. Pfister 9 7 0 03 Jul 2019
An innovative adaptive kriging approach for efficient binary classification of mechanical problems J. Fuhg A. Fau AI4CE 20 2 0 02 Jul 2019
Mixed-Variable Bayesian Optimization Erik A. Daxberger Anastasia Makarova M. Turchetta Andreas Krause 18 51 0 02 Jul 2019
Variational Federated Multi-Task Learning Luca Corinzia Ami Beuret J. M. Buhmann FedML 27 159 0 14 Jun 2019
Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical Bayes R. Krishnan Mahesh Subedar Omesh Tickoo BDL 20 46 0 12 Jun 2019
On the Universality of Noiseless Linear Estimation with Respect to the Measurement Matrix A. Abbara Antoine Baker Florent Krzakala Lenka Zdeborová 17 12 0 11 Jun 2019
Assessing the Robustness of Bayesian Dark Knowledge to Posterior Uncertainty Meet P. Vadera Benjamin M. Marlin BDL UQCV 6 1 0 04 Jun 2019
Multi-objective Bayesian Optimization using Pareto-frontier Entropy Shinya Suzuki Shion Takeno T. Tamura Kazuki Shitara Masayuki Karasuyama 17 73 0 01 Jun 2019
Adversarial Robustness Guarantees for Classification with Gaussian Processes Arno Blaas A. Patané Luca Laurenti L. Cardelli Marta Z. Kwiatkowska Stephen J. Roberts GP AAML 13 21 0 28 May 2019
Interpretable deep Gaussian processes with moments Chi-Ken Lu Scott Cheng-Hsin Yang Xiaoran Hao Patrick Shafto 13 19 0 27 May 2019
Precision-Recall Curves Using Information Divergence Frontiers Josip Djolonga Mario Lucic Marco Cuturi Olivier Bachem Olivier Bousquet Sylvain Gelly 15 4 0 26 May 2019
Replicated Vector Approximate Message Passing For Resampling Problem Takashi Takahashi Y. Kabashima 6 4 0 23 May 2019
Fast online 3D reconstruction of dynamic scenes from individual single-photon detection events Y. Altmann S. Mclaughlin Michael E. Davies 3DV 11 22 0 08 May 2019
Compressed sensing reconstruction using Expectation Propagation Alfredo Braunstein Anna Paola Muntoni A. Pagnani Mirko Pieropan 7 11 0 10 Apr 2019
A Generalization Bound for Online Variational Inference Badr-Eddine Chérief-Abdellatif Pierre Alquier Mohammad Emtiyaz Khan BDL 15 25 0 08 Apr 2019
Generalized Variational Inference: Three arguments for deriving new Posteriors Jeremias Knoblauch Jack Jewson Theodoros Damoulas DRL BDL 36 105 0 03 Apr 2019
Probabilistic Forecasting of Sensory Data with Generative Adversarial Networks - ForGAN Alireza Koochali P. Schichtel Sheraz Ahmed Andreas Dengel AI4TS 22 72 0 29 Mar 2019
Analysis of Spectral Methods for Phase Retrieval with Random Orthogonal Matrices Rishabh Dudeja Milad Bakhshizadeh Junjie Ma A. Maleki 19 20 0 07 Mar 2019
Asymptotics of MAP Inference in Deep Networks Parthe Pandit Mojtaba Sahraee S. Rangan A. Fletcher 18 21 0 01 Mar 2019
Multifidelity Bayesian Optimization for Binomial Output L. Matyushin Alexey Zaytsev O. Alenkin Andrey Ustuzhanin 17 0 0 19 Feb 2019
Asymptotic Consistency of $α-$ Rényi-Approximate Posteriors Prateek Jaiswal Vinayak A. Rao Harsha Honnappa 8 12 0 05 Feb 2019
Variational Bayesian Decision-making for Continuous Utilities Tomasz Kuśmierczyk J. Sakaya Arto Klami 11 21 0 02 Feb 2019
End-to-End Probabilistic Inference for Nonstationary Audio Analysis William J. Wilkinson Michael Riis Andersen Joshua D. Reiss D. Stowell Arno Solin 6 5 0 31 Jan 2019
Multi-fidelity Bayesian Optimization with Max-value Entropy Search and its parallelization Shion Takeno H. Fukuoka Yuhki Tsukada T. Koyama M. Shiga Ichiro Takeuchi Masayuki Karasuyama 8 40 0 24 Jan 2019
A Review on Quantile Regression for Stochastic Computer Experiments Léonard Torossian Victor Picheny Robert Faivre Aurélien Garivier MQ 11 0 0 23 Jan 2019
Mixed Variational Inference Nikolaos Gianniotis BDL 6 1 0 15 Jan 2019
Posterior inference unchained with EL_2O U. Seljak Byeonghee Yu 9 10 0 14 Jan 2019
Graphical model inference: Sequential Monte Carlo meets deterministic approximations Fredrik Lindsten Jouni Helske M. Vihola 6 13 0 08 Jan 2019
Adversarial Learning of a Sampler Based on an Unnormalized Distribution Chunyuan Li Ke Bai Jianqiao Li Guoyin Wang Changyou Chen Lawrence Carin 14 10 0 03 Jan 2019
A Bayesian Additive Model for Understanding Public Transport Usage in Special Events Filipe Rodrigues S. Borysov B. Ribeiro Francisco Câmara Pereira AI4TS 14 50 0 20 Dec 2018
Computational Solutions for Bayesian Inference in Mixture Models G. Celeux K. Kamary G. Malsiner‐Walli Jean-Michel Marin Christian P. Robert 8 17 0 18 Dec 2018
Efficient and Robust Machine Learning for Real-World Systems Franz Pernkopf Wolfgang Roth Matthias Zöhrer Lukas Pfeifenberger Günther Schindler Holger Froening Sebastian Tschiatschek Robert Peharz Matthew Mattina Zoubin Ghahramani OOD 27 1 0 05 Dec 2018
Partitioned Variational Inference: A unified framework encompassing federated and continual learning T. Bui Cuong V Nguyen S. Swaroop Richard Turner FedML 16 55 0 27 Nov 2018