Expectation Propagation for approximate Bayesian inference

10 January 2013

Papers citing "Expectation Propagation for approximate Bayesian inference"

50 / 491 papers shown

Title
On the role of synaptic stochasticity in training low-precision neural networks Carlo Baldassi Federica Gerace H. Kappen C. Lucibello Luca Saglietti Enzo Tartaglione R. Zecchina 9 23 0 26 Oct 2017
Scalable Bayesian regression in high dimensions with multiple data sources K. Perrakis S. Mukherjee The Alzheimer's Disease Neuroimaging Initiative 24 4 0 02 Oct 2017
Remote Sensing Image Classification with Large Scale Gaussian Processes Pablo Morales-Álvarez Adrián Pérez-Suay Rafael Molina Gustau Camps-Valls 14 41 0 02 Oct 2017
PASS-GLM: polynomial approximate sufficient statistics for scalable Bayesian GLM inference Jonathan H. Huggins Ryan P. Adams Tamara Broderick 24 32 0 26 Sep 2017
Approximate Bayesian Inference in Linear State Space Models for Intermittent Demand Forecasting at Scale Matthias Seeger Syama Sundar Rangapuram Bernie Wang David Salinas Jan Gasthaus Tim Januschowski Valentin Flunkert BDL 40 18 0 22 Sep 2017
Variational Gaussian Approximation for Poisson Data Simon Arridge Kazufumi Ito Bangti Jin Chen Zhang 6 22 0 18 Sep 2017
Variational Inference for Logical Inference Guy Edward Toh Emerson Ann A. Copestake NAI 26 7 0 01 Sep 2017
Learning Inference Models for Computer Vision Varun Jampani BDL 22 1 0 31 Aug 2017
Towards Bursting Filter Bubble via Contextual Risks and Uncertainties Rikiya Takahashi Shunan Zhang 6 1 0 30 Jun 2017
Scalable Multi-Class Gaussian Process Classification using Expectation Propagation Carlos Villacampa-Calvo Daniel Hernández-Lobato 18 19 0 22 Jun 2017
Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control Sanket Kamthe M. Deisenroth 8 216 0 20 Jun 2017
On the correspondence between thermodynamics and inference Colin H. LaMont Paul A. Wiggins 15 26 0 05 Jun 2017
Streaming Bayesian inference: theoretical limits and mini-batch approximate message-passing Andre Manoel Florent Krzakala Eric W. Tramel Lenka Zdeborová 27 13 0 02 Jun 2017
A statistical physics approach to learning curves for the Inverse Ising problem Ludovica Bachschmid-Romano Manfred Opper 33 13 0 15 May 2017
Nonlinear Kalman Filtering with Divergence Minimization San Gultekin John Paisley 16 40 0 01 May 2017
Structured Sparse Modelling with Hierarchical GP Danil Kuzin Olga Isupova Lyudmila Mihaylova 9 1 0 27 Apr 2017
Continuously tempered Hamiltonian Monte Carlo Matthew M. Graham Amos J. Storkey 27 26 0 11 Apr 2017
Practical Bayesian Optimization for Variable Cost Objectives Mark McLeod Michael A. Osborne Stephen J. Roberts 17 32 0 13 Mar 2017
Conjugate-Computation Variational Inference : Converting Variational Inference in Non-Conjugate Models to Inferences in Conjugate Models Mohammad Emtiyaz Khan Wu Lin BDL 19 135 0 13 Mar 2017
Dropout Inference in Bayesian Neural Networks with Alpha-divergences Yingzhen Li Y. Gal UQCV BDL 46 195 0 08 Mar 2017
Multiplicative Normalizing Flows for Variational Bayesian Neural Networks Christos Louizos Max Welling BDL 16 453 0 06 Mar 2017
Iterative Bayesian Learning for Crowdsourced Regression Jungseul Ok Sewoong Oh Yunhun Jang Jinwoo Shin Yung Yi 21 3 0 28 Feb 2017
Approximate Inference with Amortised MCMC Yingzhen Li Richard Turner Qiang Liu BDL 19 61 0 27 Feb 2017
Variational Inference using Implicit Distributions Ferenc Huszár DRL GAN 11 135 0 27 Feb 2017
Probabilistic Sensor Fusion for Ambient Assisted Living Tom Diethe Niall Twomey Meelis Kull Peter A. Flach I. Craddock 11 22 0 04 Feb 2017
Deep Probabilistic Programming Dustin Tran Matthew D. Hoffman Rif A. Saurous E. Brevdo Kevin Patrick Murphy David M. Blei BDL 33 193 0 13 Jan 2017
Conditional Central Limit Theorems for Gaussian Projections Galen Reeves 16 25 0 29 Dec 2016
Expectation Propagation performs a smoothed gradient descent Guillaume P. Dehaene BDL UQCV 6 3 0 15 Dec 2016
Adversarial Message Passing For Graphical Models Theofanis Karaletsos GAN 24 29 0 15 Dec 2016
Knowledge Elicitation via Sequential Probabilistic Inference for High-Dimensional Prediction Pedram Daee Tomi Peltola Marta Soare Samuel Kaski 14 33 0 10 Dec 2016
Improved prediction accuracy for disease risk mapping using Gaussian Process stacked generalisation Samir Bhatt E. Cameron Seth R Flaxman D. Weiss David L. Smith P. Gething 18 104 0 10 Dec 2016
Structured Filtering C. Granade N. Wiebe 19 6 0 01 Dec 2016
Inference for log Gaussian Cox processes using an approximate marginal posterior Shinichiro Shirota A. Gelfand 21 7 0 30 Nov 2016
On numerical approximation schemes for expectation propagation A. Roche 22 0 0 14 Nov 2016
Variational Inference via $χ$ -Upper Bound Minimization Adji Bousso Dieng Dustin Tran Rajesh Ranganath John Paisley David M. Blei BDL 81 36 0 01 Nov 2016
Edward: A library for probabilistic modeling, inference, and criticism Dustin Tran A. Kucukelbir Adji Bousso Dieng Maja R. Rudolph Dawen Liang David M. Blei 16 300 0 31 Oct 2016
Moment Matching Based Conjugacy Approximation for Bayesian Ranking and Selection Qiong Zhang Yongjia Song 17 10 0 28 Oct 2016
Operator Variational Inference Rajesh Ranganath Jaan Altosaar Dustin Tran David M. Blei 15 116 0 27 Oct 2016
Optimal Encoding and Decoding for Point Process Observations: an Approximate Closed-Form Filter Y. Harel Ron Meir Manfred Opper 12 3 0 12 Sep 2016
Importance sampling type estimators based on approximate marginal MCMC M. Vihola Jouni Helske Jordan Franks 21 25 0 08 Sep 2016
Predictive Entropy Search for Multi-objective Bayesian Optimization with Constraints Daniel Hernández-Lobato Daniel Hernández-Lobato 18 113 0 05 Sep 2016
Generic Inference in Latent Gaussian Process Models Edwin V. Bonilla K. Krauth Amir Dezfouli BDL 23 28 0 02 Sep 2016
Skew-t Filter and Smoother with Improved Covariance Matrix Approximation Henri Nurminen Tohid Ardeshiri R. Piché Fredrik K. Gustafsson 12 44 0 26 Aug 2016
Self-Averaging Expectation Propagation Burak Çakmak Manfred Opper B. Fleury Ole Winther 22 9 0 23 Aug 2016
The Bayesian Low-Rank Determinantal Point Process Mixture Model Mike Gartrell Ulrich Paquet Noam Koenigstein BDL 16 0 0 15 Aug 2016
Branching Gaussian Processes with Applications to Spatiotemporal Reconstruction of 3D Trees K. Simek R. Palanivelu Kobus Barnard 11 5 0 14 Aug 2016
From Dependence to Causation David Lopez-Paz OOD CML 58 25 0 12 Jul 2016
Approximate Marginal Posterior for Log Gaussian Cox Processes Shinichiro Shirota A. Gelfand 18 2 0 26 Jun 2016
Post-Inference Prior Swapping W. Neiswanger Eric P. Xing 14 1 0 02 Jun 2016
Applications of Probabilistic Programming (Master's thesis, 2015) Yura N. Perov 21 4 0 31 May 2016