Expectation Propagation for approximate Bayesian inference

10 January 2013

Papers citing "Expectation Propagation for approximate Bayesian inference"

50 / 491 papers shown

Title
Featuremetric benchmarking: Quantum computer benchmarks based on circuit features Timothy Proctor Anh Tran Xingxin Liu Aditya Dhumuntarao Stefan Seritan Alaina Green Norbert M Linke 29 0 0 17 Apr 2025
Amortized In-Context Bayesian Posterior Estimation Sarthak Mittal Niels Leif Bracher Guillaume Lajoie P. Jaini Marcus A. Brubaker 62 1 0 10 Feb 2025
Distribution Transformers: Fast Approximate Bayesian Inference With On-The-Fly Prior Adaptation George Whittle Juliusz Ziomek Jacob Rawling Michael A. Osborne 94 2 0 04 Feb 2025
Pareto-frontier Entropy Search with Variational Lower Bound Maximization Masanori Ishikura Masayuki Karasuyama 63 0 0 31 Jan 2025
Unifying AMP Algorithms for Rotationally-Invariant Models Songbin Liu Junjie Ma 77 0 0 02 Dec 2024
Prediction of Acoustic Communication Performance for AUVs using Gaussian Process Classification Yifei Gao Harun Yetkin McMahon James D. Stilwell 21 0 0 12 Nov 2024
Inclusive KL Minimization: A Wasserstein-Fisher-Rao Gradient Flow Perspective Jia-Jie Zhu 68 1 0 31 Oct 2024
Batched Bayesian optimization by maximizing the probability of including the optimum Jenna C. Fromer Runzhong Wang Mrunali Manjrekar Austin Tripp José Miguel Hernández-Lobato Connor W. Coley 47 0 0 08 Oct 2024
Skew-symmetric approximations of posterior distributions Francesco Pozza Daniele Durante Botond Szabó 39 2 0 21 Sep 2024
Computationally Efficient Estimation of Large Probit Models Patrick Ding Guido Imbens Zhaonan Qu Yinyu Ye 29 0 0 12 Jul 2024
Scalable expectation propagation for generalized linear models Niccolò Anceschi A. Fasano Beatrice Franzolini Giovanni Rebaudo 35 0 0 02 Jul 2024
Approximation-Aware Bayesian Optimization Natalie Maus Kyurae Kim Geoff Pleiss David Eriksson John P. Cunningham Jacob R. Gardner 29 2 0 06 Jun 2024
Exploring the Practicality of Federated Learning: A Survey Towards the Communication Perspective Khiem H. Le Nhan Luong-Ha Manh Nguyen-Duc Danh Le-Phuoc Cuong D. Do Kok-Seng Wong FedML 29 1 0 30 May 2024
Robust Entropy Search for Safe Efficient Bayesian Optimization D. Weichert Alexander Kister Sebastian Houben Patrick Link G. Ernis AAML 57 0 0 29 May 2024
Variational Bayes for Federated Continual Learning Dezhong Yao Sanmu Li Yutong Dai Zhiqiang Xu Shengshan Hu Peilin Zhao Lichao Sun FedML 56 1 0 23 May 2024
Doubly Adaptive Importance Sampling W. van den Boom Andrea Cremaschi Alexandre H. Thiery 26 0 0 29 Apr 2024
Analytical Approximation of the ELBO Gradient in the Context of the Clutter Problem Roumen Nikolaev Popov 24 0 0 16 Apr 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
Circular Belief Propagation for Approximate Probabilistic Inference Vincent Bouttier R. Jardri S. Denéve 25 0 0 17 Mar 2024
Stacking Factorizing Partitioned Expressions in Hybrid Bayesian Network Models Peng Lin M. Neil Norman E. Fenton 20 0 0 23 Feb 2024
Safe Active Learning for Time-Series Modeling with Gaussian Processes Christoph Zimmer Mona Meister D. Nguyen-Tuong AI4TS 27 52 0 09 Feb 2024
Bayesian Uncertainty for Gradient Aggregation in Multi-Task Learning Idan Achituve I. Diamant Arnon Netzer Gal Chechik Ethan Fetaya UQCV 32 4 0 06 Feb 2024
Bootstrap Your Own Variance Polina Turishcheva Jason Ramapuram Sinead Williamson Dan Busbridge Eeshan Gunesh Dhekane Russ Webb UQCV 26 0 0 06 Dec 2023
Constrained Bayesian Optimization Under Partial Observations: Balanced Improvements and Provable Convergence Shengbo Wang Ke Li 18 11 0 06 Dec 2023
Entropy and the Kullback-Leibler Divergence for Bayesian Networks: Computational Complexity and Efficient Implementation Marco Scutari 16 2 0 29 Nov 2023
Multi-Objective Bayesian Optimization with Active Preference Learning Ryota Ozaki Kazuki Ishikawa Youhei Kanzaki Shinya Suzuki Shion Takeno Ichiro Takeuchi Masayuki Karasuyama 25 7 0 22 Nov 2023
Functional Bayesian Tucker Decomposition for Continuous-indexed Tensor Data Shikai Fang Xin Yu Zheng Wang Shibo Li R. Kirby Shandian Zhe 24 1 0 08 Nov 2023
Riemannian Laplace Approximation with the Fisher Metric Hanlin Yu Marcelo Hartmann Bernardo Williams M. Girolami Arto Klami 32 3 0 05 Nov 2023
Variational Inference for Sparse Poisson Regression Mitra Kharabati Morteza Amini 32 1 0 02 Nov 2023
Bridging the Gap Between Variational Inference and Wasserstein Gradient Flows Mingxuan Yi Song Liu DRL 33 8 0 31 Oct 2023
Streaming Factor Trajectory Learning for Temporal Tensor Decomposition Shikai Fang Xin Yu Shibo Li Zheng Wang R. Kirby Shandian Zhe AI4TS 27 3 0 25 Oct 2023
PRIOR: Personalized Prior for Reactivating the Information Overlooked in Federated Learning Mingjia Shi Yuhao Zhou Kai Wang Huaizheng Zhang Shudong Huang Qing Ye Jiangcheng Lv 26 9 0 13 Oct 2023
LARA: A Light and Anti-overfitting Retraining Approach for Unsupervised Time Series Anomaly Detection Feiyi Chen Zhen Qin Yingying Zhang Shuiguang Deng Lunting Fan Guansong Pang Qingsong Wen AI4TS 14 6 0 09 Oct 2023
Equation Discovery with Bayesian Spike-and-Slab Priors and Efficient Kernels Da Long Wei W. Xing Aditi S. Krishnapriyan R. Kirby Shandian Zhe Michael W. Mahoney 18 0 0 09 Oct 2023
Inferring Inference Rajkumar Vasudeva Raju Zhe Li Scott W. Linderman Xaq Pitkow 22 1 0 04 Oct 2023
Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization Dinghuai Zhang Ricky Tian Qi Chen Cheng-Hao Liu Aaron C. Courville Yoshua Bengio 34 40 0 04 Oct 2023
An Easy Rejection Sampling Baseline via Gradient Refined Proposals Edward Raff Mark McLean James Holt 15 0 0 30 Sep 2023
Deep Networks as Denoising Algorithms: Sample-Efficient Learning of Diffusion Models in High-Dimensional Graphical Models Song Mei Yuchen Wu DiffM 31 26 0 20 Sep 2023
Total Variation Distance Meets Probabilistic Inference Arnab Bhattacharyya Sutanu Gayen Kuldeep S. Meel Dimitrios Myrisiotis A. Pavan N. V. Vinodchandran 13 4 0 17 Sep 2023
Amortised Inference in Bayesian Neural Networks Tommy Rochussen UQCV BDL 28 0 0 06 Sep 2023
Expectation propagation for the smoothing distribution in dynamic probit Niccolò Anceschi A. Fasano Giovanni Rebaudo 27 0 0 04 Sep 2023
BayOTIDE: Bayesian Online Multivariate Time series Imputation with functional decomposition Shikai Fang Qingsong Wen Yingtao Luo Shandian Zhe Liang Sun AI4TS 27 5 0 28 Aug 2023
A State-Space Perspective on Modelling and Inference for Online Skill Rating Samuel Duffield Samuel Power Lorenzo Rimella 18 6 0 04 Aug 2023
Variational Inference with Gaussian Score Matching Chirag Modi C. Margossian Yuling Yao Robert Mansel Gower David M. Blei Lawrence K. Saul 16 12 0 15 Jul 2023
Human-in-the-Loop Optimization for Deep Stimulus Encoding in Visual Prostheses Jacob Granley T. Fauvel M. Chalk M. Beyeler 13 9 0 16 Jun 2023
Realising Synthetic Active Inference Agents, Part I: Epistemic Objectives and Graphical Specification Language Magnus T. Koudahl T. V. D. Laar Bert De Vries 24 1 0 13 Jun 2023
Automating Model Comparison in Factor Graphs Bart Van Erp Wouter W. L. Nuijten T. V. D. Laar Bert De Vries 16 1 0 09 Jun 2023
Improving Hyperparameter Learning under Approximate Inference in Gaussian Process Models Rui Li S. T. John Arno Solin BDL 20 3 0 07 Jun 2023
Variational Gaussian Process Diffusion Processes Prakhar Verma Vincent Adam Arno Solin DiffM 22 5 0 03 Jun 2023
On the Convergence of Coordinate Ascent Variational Inference A. Bhattacharya D. Pati Yun Yang 17 10 0 01 Jun 2023