Expectation Propagation for approximate Bayesian inference

10 January 2013

Papers citing "Expectation Propagation for approximate Bayesian inference"

50 / 491 papers shown

Title
Approximate Inference via Clustering Qianqian Song 31 0 0 28 Nov 2021
Differentially private stochastic expectation propagation (DP-SEP) Margarita Vinaroz Mijung Park 25 1 0 25 Nov 2021
Low-rank variational Bayes correction to the Laplace method J. van Niekerk Haavard Rue BDL 13 13 0 25 Nov 2021
Dual Parameterization of Sparse Variational Gaussian Processes Vincent Adam Paul E. Chang Mohammad Emtiyaz Khan Arno Solin 19 20 0 05 Nov 2021
Towards Designing Optimal Sensing Matrices for Generalized Linear Inverse Problems Junjie Ma Ji Xu A. Maleki 11 3 0 05 Nov 2021
Variational Inference with Holder Bounds Junya Chen Danni Lu Zidi Xiu Ke Bai Lawrence Carin Chenyang Tao 19 6 0 04 Nov 2021
A derivation of variational message passing (VMP) for latent Dirichlet allocation (LDA) Rebecca M. C. Taylor D. Coetsee J. D. Preez 15 0 0 02 Nov 2021
Deep learning via message passing algorithms based on belief propagation C. Lucibello Fabrizio Pittorino Gabriele Perugini R. Zecchina 43 14 0 27 Oct 2021
Online Variational Filtering and Parameter Learning Andrew Campbell Yuyang Shi Tom Rainforth Arnaud Doucet BDL 30 21 0 26 Oct 2021
Conditional Variational Autoencoder for Learned Image Reconstruction Chen Zhang Riccardo Barbano Bangti Jin DRL 15 19 0 22 Oct 2021
PriorVAE: Encoding spatial priors with VAEs for small-area estimation Elizaveta Semenova Yidan Xu A. Howes T. Rashid Samir Bhatt Swapnil Mishra Seth Flaxman 17 11 0 20 Oct 2021
Is MC Dropout Bayesian? Loic Le Folgoc V. Baltatzis S. Desai A. Devaraj S. Ellis O. M. Manzanera A. Nair Huaqi Qiu J. Schnabel Ben Glocker BDL OOD UQCV 30 39 0 08 Oct 2021
Fast Scalable Image Restoration using Total Variation Priors and Expectation Propagation D. Yao S. Mclaughlin Y. Altmann 13 6 0 04 Oct 2021
Conditional Deep Gaussian Processes: empirical Bayes hyperdata learning Chi-Ken Lu Patrick Shafto BDL 27 4 0 01 Oct 2021
Bayesian Transfer Learning: An Overview of Probabilistic Graphical Models for Transfer Learning Junyu Xuan Jie Lu Guangquan Zhang BDL 164 7 0 27 Sep 2021
Graph-based Approximate Message Passing Iterations Cédric Gerbelot Raphael Berthier 32 46 0 24 Sep 2021
A Survey on Cost Types, Interaction Schemes, and Annotator Performance Models in Selection Algorithms for Active Learning in Classification M. Herde Denis Huseljic Bernhard Sick A. Calma 37 25 0 23 Sep 2021
Bayesian analysis of the prevalence bias: learning and predicting from imbalanced data Loic Le Folgoc V. Baltatzis A. Alansary S. Desai A. Devaraj ... O. M. Manzanera F. Kanavati A. Nair J. Schnabel Ben Glocker 8 0 0 31 Jul 2021
Generalization of graph network inferences in higher-order graphical models Yicheng Fei Xaq Pitkow 16 0 0 12 Jul 2021
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 38 1,111 0 07 Jul 2021
A visual introduction to Gaussian Belief Propagation Joseph Ortiz Talfan Evans Andrew J. Davison 15 32 0 05 Jul 2021
Patch-Based Image Restoration using Expectation Propagation Dan Yao S. Mclaughlin Y. Altmann DiffM 11 5 0 18 Jun 2021
Probabilistic DAG Search Julia Grosse Cheng Zhang Philipp Hennig 18 4 0 16 Jun 2021
Post-hoc loss-calibration for Bayesian neural networks Meet P. Vadera S. Ghosh Kenney Ng Benjamin M. Marlin UQCV BDL 43 7 0 13 Jun 2021
Nonlinear Hawkes Processes in Time-Varying System Feng Zhou Quyu Kong Yixuan Zhang Cheng Feng Jun Zhu 14 6 0 09 Jun 2021
Energy-Based Learning for Cooperative Games, with Applications to Valuation Problems in Machine Learning Yatao Bian Yu Rong Tingyang Xu Jiaxiang Wu Andreas Krause Junzhou Huang 37 16 0 05 Jun 2021
Memory Approximate Message Passing Lei Liu Shunqi Huang B. Kurkoski 13 26 0 04 Jun 2021
Latent Gaussian Model Boosting Fabio Sigrist AI4CE 14 23 0 19 May 2021
Laplace Matching for fast Approximate Inference in Latent Gaussian Models Marius Hobbhahn Philipp Hennig BDL 11 2 0 07 May 2021
Matrix completion based on Gaussian parameterized belief propagation Koki Okajima Y. Kabashima 6 0 0 01 May 2021
Degenerate Gaussian factors for probabilistic inference J. C. Schoeman C. E. V. Daalen J. D. Preez 13 3 0 30 Apr 2021
DisCo RL: Distribution-Conditioned Reinforcement Learning for General-Purpose Policies Soroush Nasiriany Vitchyr H. Pong Ashvin Nair Alexander Khazatsky Glen Berseth Sergey Levine OffRL 63 14 0 23 Apr 2021
Active and sparse methods in smoothed model checking Paul Piho J. Hillston 14 2 0 20 Apr 2021
Adversarial Robustness Guarantees for Gaussian Processes A. Patané Arno Blaas Luca Laurenti L. Cardelli Stephen J. Roberts Marta Z. Kwiatkowska GP AAML 95 9 0 07 Apr 2021
Sparse Algorithms for Markovian Gaussian Processes William J. Wilkinson Arno Solin Vincent Adam 13 12 0 19 Mar 2021
Meta-Learning an Inference Algorithm for Probabilistic Programs Gwonsoo Che Hongseok Yang TPM 16 1 0 01 Mar 2021
BayesPerf: Minimizing Performance Monitoring Errors Using Bayesian Statistics Subho Sankar Banerjee Saurabh Jha Zbigniew T. Kalbarczyk R. Iyer 11 12 0 22 Feb 2021
Sequential- and Parallel- Constrained Max-value Entropy Search via Information Lower Bound Shion Takeno T. Tamura Kazuki Shitara Masayuki Karasuyama 37 17 0 19 Feb 2021
Chance-Constrained Active Inference T. V. D. Laar Ismail Senöz Ayça Özçelikkale H. Wymeersch AI4CE 39 7 0 17 Feb 2021
A Compositional Atlas of Tractable Circuit Operations: From Simple Transformations to Complex Information-Theoretic Queries Antonio Vergari YooJung Choi Anji Liu Stefano Teso Guy Van den Broeck TPM 23 12 0 11 Feb 2021
Low Complexity Approximate Bayesian Logistic Regression for Sparse Online Learning G. Shamir Wojtek Szpankowski 6 6 0 28 Jan 2021
Phase Retrieval using Expectation Consistent Signal Recovery Algorithm based on Hypernetwork Chang-Jen Wang Chao-Kai Wen Shang-Ho S. Tsai Shi Jin Geoffrey Ye Li 19 5 0 12 Jan 2021
Solving Common-Payoff Games with Approximate Policy Iteration Samuel Sokota Edward Lockhart Finbarr Timbers Elnaz Davoodi Ryan DÓrazio Neil Burch Martin Schmid Michael Bowling Marc Lanctot 42 22 0 11 Jan 2021
A Multilayer Correlated Topic Model Ye Tian 14 1 0 02 Jan 2021
Memory AMP Lei Liu Shunqi Huang B. Kurkoski 10 52 0 20 Dec 2020
Are we Forgetting about Compositional Optimisers in Bayesian Optimisation? Antoine Grosnit Alexander I. Cowen-Rivers Rasul Tutunov Ryan-Rhys Griffiths Jun Wang Haitham Bou-Ammar 19 13 0 15 Dec 2020
Approximate Cross-validated Mean Estimates for Bayesian Hierarchical Regression Models Amy Zhang L. Bao Changcheng Li M. Daniels 6 1 0 29 Nov 2020
Improved Max-value Entropy Search for Multi-objective Bayesian Optimization with Constraints Daniel Fernández-Sánchez Eduardo C. Garrido-Merchán Daniel Hernández-Lobato 12 31 0 02 Nov 2020
Predicting Infectiousness for Proactive Contact Tracing Yoshua Bengio Prateek Gupta Tegan Maharaj Nasim Rahaman Martin Weiss ... Irina Rish Bernhard Schölkopf Abhinav Sharma Jian Tang Andrew Robert Williams 37 15 0 23 Oct 2020
Flexible mean field variational inference using mixtures of non-overlapping exponential families J. Spence 17 4 0 14 Oct 2020