Stochastic Variational Inference

29 June 2012

Matt Hoffman

Papers citing "Stochastic Variational Inference"

50 / 1,065 papers shown

Title
Variational Inference with Gaussian Score Matching Chirag Modi C. Margossian Yuling Yao Robert Mansel Gower David M. Blei Lawrence K. Saul 18 12 0 15 Jul 2023
Drug Discovery under Covariate Shift with Domain-Informed Prior Distributions over Functions Leo Klarner Tim G. J. Rudner M. Reutlinger Torsten Schindler Garrett M. Morris Charlotte M. Deane Yee Whye Teh OOD BDL 15 9 0 14 Jul 2023
Embracing the chaos: analysis and diagnosis of numerical instability in variational flows Zuheng Xu Trevor Campbell 35 2 0 12 Jul 2023
Function-Space Regularization for Deep Bayesian Classification J. Lin Joe Watson Pascal Klink Jan Peters UQCV BDL 41 1 0 12 Jul 2023
A probabilistic, data-driven closure model for RANS simulations with aleatoric, model uncertainty A. Agrawal P. Koutsourelakis AI4CE 24 16 0 05 Jul 2023
Causal Structure Learning by Using Intersection of Markov Blankets Yiran Dong Chuanhou Gao CML 21 0 0 01 Jul 2023
Unbiased Learning of Deep Generative Models with Structured Discrete Representations H. Bendekgey Gabriel Hope Erik B. Sudderth OCL BDL DRL 24 1 0 14 Jun 2023
A Cloud-based Machine Learning Pipeline for the Efficient Extraction of Insights from Customer Reviews Róbert Lakatos G. Bogacsovics B. Harangi István Lakatos Attila Tiba János Tóth Marianna Szabó András Hajdu 11 1 0 13 Jun 2023
Deep Gaussian Mixture Ensembles Yousef El-Laham Niccolò Dalmasso Elizabeth Fons Svitlana Vyetrenko BDL UQCV 33 2 0 12 Jun 2023
Additive Multi-Index Gaussian process modeling, with application to multi-physics surrogate modeling of the quark-gluon plasma Kevin Li Simon Mak J. Paquet S. Bass AI4CE 11 10 0 11 Jun 2023
Push: Concurrent Probabilistic Programming for Bayesian Deep Learning Daniel Huang Christian Camaño Jonathan Tsegaye Jonathan Austin Gale AI4CE 35 0 0 10 Jun 2023
Automating Model Comparison in Factor Graphs Bart Van Erp Wouter W. L. Nuijten T. V. D. Laar Bert De Vries 18 1 0 09 Jun 2023
Provable convergence guarantees for black-box variational inference Justin Domke Guillaume Garrigos Robert Mansel Gower 18 18 0 04 Jun 2023
On the Convergence of Coordinate Ascent Variational Inference A. Bhattacharya D. Pati Yun Yang 22 10 0 01 Jun 2023
R-VGAL: A Sequential Variational Bayes Algorithm for Generalised Linear Mixed Models Bao Anh Vu David Gunawan A. Zammit‐Mangion DRL 12 1 0 01 Jun 2023
A Study of Bayesian Neural Network Surrogates for Bayesian Optimization Y. Li Tim G. J. Rudner A. Wilson BDL 32 28 0 31 May 2023
Scalable Learning of Latent Language Structure With Logical Offline Cycle Consistency M. Crouse Ramón Fernández Astudillo Tahira Naseem Subhajit Chaudhury Pavan Kapanipathi Salim Roukos Alexander G. Gray OffRL 22 0 0 31 May 2023
Parameter Estimation in DAGs from Incomplete Data via Optimal Transport Vy Vo Trung Le L. Vuong He Zhao Edwin V. Bonilla Dinh Q. Phung OT 21 4 0 25 May 2023
Learning Rate Free Sampling in Constrained Domains Louis Sharrock Lester W. Mackey Christopher Nemeth 41 2 0 24 May 2023
Wasserstein Gaussianization and Efficient Variational Bayes for Robust Bayesian Synthetic Likelihood Nhat-Minh Nguyen Minh-Ngoc Tran Christopher C. Drovandi David J. Nott 9 1 0 24 May 2023
Fast Variational Inference for Bayesian Factor Analysis in Single and Multi-Study Settings Blake Hansen Alejandra Avalos-Pacheco Massimiliano Russo Roberta De Vito 15 4 0 22 May 2023
Real-Time Variational Method for Learning Neural Trajectory and its Dynamics Matthew Dowling Yuan Zhao Il Memming Park BDL OffRL 21 6 0 18 May 2023
A Variational Perspective on Solving Inverse Problems with Diffusion Models Morteza Mardani Jiaming Song Jan Kautz Arash Vahdat DiffM 24 126 0 07 May 2023
Variational Nonlinear Kalman Filtering with Unknown Process Noise Covariance Hua Lan Jinjie Hu Zengfu Wang Q. Cheng 13 10 0 06 May 2023
Variational Bayes Made Easy Mohammad Emtiyaz Khan BDL 29 1 0 27 Apr 2023
Machine Learning and the Future of Bayesian Computation Steven Winter Trevor Campbell Lizhen Lin Sanvesh Srivastava David B. Dunson TPM 47 4 0 21 Apr 2023
Bayes Hilbert Spaces for Posterior Approximation George Wynne 8 1 0 18 Apr 2023
NF-ULA: Langevin Monte Carlo with Normalizing Flow Prior for Imaging Inverse Problems Ziruo Cai Junqi Tang Subhadip Mukherjee Jinglai Li Carola Bibiane Schönlieb Xiaoqun Zhang AI4CE 36 3 0 17 Apr 2023
Black Box Variational Inference with a Deterministic Objective: Faster, More Accurate, and Even More Black Box Ryan Giordano Martin Ingram Tamara Broderick 64 12 0 11 Apr 2023
Learning Sparsity of Representations with Discrete Latent Variables Zhao Xu Daniel Oñoro-Rubio G. Serra Mathias Niepert 13 0 0 03 Apr 2023
Fast inference of latent space dynamics in huge relational event networks I. Artico Ernst C. Wit BDL 21 1 0 29 Mar 2023
Interacting Particle Langevin Algorithm for Maximum Marginal Likelihood Estimation Ö. Deniz Akyildiz F. R. Crucinio Mark Girolami Tim Johnston Sotirios Sabanis 32 12 0 23 Mar 2023
Wasserstein Auto-encoded MDPs: Formal Verification of Efficiently Distilled RL Policies with Many-sided Guarantees Florent Delgrange Ann Nowé Guillermo A. Pérez OffRL 29 4 0 22 Mar 2023
Bayesian Beta-Bernoulli Process Sparse Coding with Deep Neural Networks Arunesh Mittal Kai Yang P. Sajda John Paisley BDL 11 0 0 14 Mar 2023
Reliable Beamforming at Terahertz Bands: Are Causal Representations the Way Forward? Christo Kurisummoottil Thomas Walid Saad 29 4 0 14 Mar 2023
Learning Energy Conserving Dynamics Efficiently with Hamiltonian Gaussian Processes M. Ross Markus Heinonen 18 2 0 03 Mar 2023
Automated Task-Time Interventions to Improve Teamwork using Imitation Learning Sang-Wook Seo Bing-zheng Han Vaibhav Unhelkar 29 6 0 01 Mar 2023
Particle-based Online Bayesian Sampling Yifan Yang Chang-rui Liu Zhengze Zhang BDL 19 7 0 28 Feb 2023
Modern Bayesian Experimental Design Tom Rainforth Adam Foster Desi R. Ivanova Freddie Bickford-Smith 37 77 0 28 Feb 2023
Natural Gradient Hybrid Variational Inference with Application to Deep Mixed Models Weiben Zhang M. Smith Worapree Maneesoonthorn Rubén Loaiza-Maya 11 1 0 27 Feb 2023
A Targeted Accuracy Diagnostic for Variational Approximations Yu-Xiang Wang Mikolaj Kasprzak Jonathan H. Huggins DRL 25 1 0 24 Feb 2023
Variational Boosted Soft Trees Tristan Cinquin Tammo Rukat Philipp Schmidt Martin Wistuba Artur Bekasov BDL UQCV 24 0 0 21 Feb 2023
Adaptive Sparse Gaussian Process Vanessa Gómez-Verdejo Emilio Parrado-Hernández M. Martínez‐Ramón 10 6 0 20 Feb 2023
Structured variational approximations with skew normal decomposable graphical models Roberto Salomone Xue Yu David J. Nott Robert Kohn 24 2 0 07 Feb 2023
Prior Density Learning in Variational Bayesian Phylogenetic Parameters Inference Amine M. Remita Golrokh Vitae Abdoulaye Baniré Diallo BDL 21 0 0 06 Feb 2023
Introducing Variational Inference in Statistics and Data Science Curriculum Vojtech Kejzlar Jingchen Hu 16 3 0 03 Jan 2023
Probabilistic quantile factor analysis Dimitris Korobilis Maximilian Schroder 12 4 0 20 Dec 2022
Variational Factorization Machines for Preference Elicitation in Large-Scale Recommender Systems Jill-Jênn Vie Tomas Rigaux H. Kashima BDL 23 1 0 20 Dec 2022
Scalable Bayesian Uncertainty Quantification for Neural Network Potentials: Promise and Pitfalls Stephan Thaler Gregor Doehner Julija Zavadlav 35 21 0 15 Dec 2022
Detection Selection Algorithm: A Likelihood based Optimization Method to Perform Post Processing for Object Detection An Fan Benjamin Ticknor Y. Amit 42 0 0 12 Dec 2022