Automatic Differentiation Variational Inference

2 March 2016

Papers citing "Automatic Differentiation Variational Inference"

50 / 73 papers shown

Title
Multi-resolution Score-Based Variational Graphical Diffusion for Causal Disaster System Modeling and Inference Xuechun Li Shan Gao Susu Xu DiffM 28 0 0 05 Apr 2025
Robust and highly scalable estimation of directional couplings from time-shifted signals Luca Ambrogioni Louis Rouillard Demian Wassermann 52 0 0 28 Jan 2025
ELBOing Stein: Variational Bayes with Stein Mixture Inference Ola Rønning Eric T. Nalisnick Christophe Ley Padhraic Smyth Thomas Hamelryck BDL 52 1 0 30 Oct 2024
Batch, match, and patch: low-rank approximations for score-based variational inference Chirag Modi Diana Cai Lawrence K. Saul BDL 37 1 0 29 Oct 2024
Noise-Aware Differentially Private Variational Inference Talal Alrawajfeh Joonas Jälkö Antti Honkela 32 0 0 25 Oct 2024
Variational Inference in Location-Scale Families: Exact Recovery of the Mean and Correlation Matrix C. Margossian Lawrence K. Saul 31 1 0 14 Oct 2024
Stochastic variance-reduced Gaussian variational inference on the Bures-Wasserstein manifold Hoang Phuc Hau Luu Hanlin Yu Bernardo Williams Marcelo Hartmann Arto Klami DRL 34 0 0 03 Oct 2024
posteriordb: Testing, Benchmarking and Developing Bayesian Inference Algorithms Måns Magnusson Jakob Torgander Paul-Christian Burkner Lu Zhang Bob Carpenter Aki Vehtari 42 6 0 06 Jul 2024
Particle Semi-Implicit Variational Inference Jen Ning Lim A. M. Johansen 43 3 0 30 Jun 2024
Torchtree: flexible phylogenetic model development and inference using PyTorch Mathieu Fourment Matthew Macaulay Christiaan J. Swanepoel Xiang Ji M. Suchard Frederick A Matsen IV BDL 29 0 0 26 Jun 2024
Demystifying SGD with Doubly Stochastic Gradients Kyurae Kim Joohwan Ko Yian Ma Jacob R. Gardner 50 0 0 03 Jun 2024
Flexible inference in heterogeneous and attributed multilayer networks Martina Contisciani Marius Hobbhahn Eleanor A. Power Philipp Hennig Caterina De Bacco 35 1 0 31 May 2024
Variational Inference for Uncertainty Quantification: an Analysis of Trade-offs C. Margossian Loucas Pillaud-Vivien Lawrence K. Saul UD 71 2 0 20 Mar 2024
Stable Training of Normalizing Flows for High-dimensional Variational Inference Daniel Andrade BDL TPM 43 1 0 26 Feb 2024
Provably Scalable Black-Box Variational Inference with Structured Variational Families Joohwan Ko Kyurae Kim W. Kim Jacob R. Gardner BDL 25 2 0 19 Jan 2024
Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference Philipp Reiser Javier Enrique Aguilar A. Guthke Paul-Christian Burkner 36 2 0 08 Dec 2023
A Knowledge Distillation Approach for Sepsis Outcome Prediction from Multivariate Clinical Time Series Anna Wong Shu Ge Nassim Oufattole Adam Dejl Megan Su A. Saeedi Li-wei H. Lehman 13 1 0 16 Nov 2023
Understanding the impact of numerical solvers on inference for differential equation models R. Creswell Katherine Shepherd Ben Lambert Gary R. Mirams Chon Lok Lei S. Tavener M. Robinson D. Gavaghan 8 5 0 03 Jul 2023
A Heavy-Tailed Algebra for Probabilistic Programming Feynman T. Liang Liam Hodgkinson Michael W. Mahoney 10 3 0 15 Jun 2023
Provable convergence guarantees for black-box variational inference Justin Domke Guillaume Garrigos Robert Mansel Gower 18 18 0 04 Jun 2023
Learning battery model parameter dynamics from data with recursive Gaussian process regression A. Aitio Dominik Jöst D. Sauer David A. Howey 9 5 0 26 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
Context-aware robot control using gesture episodes Petr Vanc Jan Kristof Behrens Karla Stepanova 22 4 0 24 Jan 2023
DPVIm: Differentially Private Variational Inference Improved Joonas Jälkö Lukas Prediger Antti Honkela Samuel Kaski 24 3 0 28 Oct 2022
Adaptive Tuning for Metropolis Adjusted Langevin Trajectories L. Riou-Durand Pavel Sountsov Jure Vogrinc C. Margossian Samuel Power 30 6 0 21 Oct 2022
Autoencoded sparse Bayesian in-IRT factorization, calibration, and amortized inference for the Work Disability Functional Assessment Battery Joshua C. Chang Carson C. Chow Julia Porcino 34 1 0 20 Oct 2022
Markov Chain Score Ascent: A Unifying Framework of Variational Inference with Markovian Gradients Kyurae Kim Jisu Oh J. Gardner Adji Bousso Dieng Hongseok Kim BDL 24 8 0 13 Jun 2022
Easy Variational Inference for Categorical Models via an Independent Binary Approximation M. Wojnowicz Shuchin Aeron Eric L. Miller M. C. Hughes 8 2 0 31 May 2022
Bayesian inference via sparse Hamiltonian flows Na Chen Zuheng Xu Trevor Campbell 30 14 0 11 Mar 2022
Partitioned Variational Inference: A Framework for Probabilistic Federated Learning Matthew Ashman T. Bui Cuong V Nguyen Efstratios Markou Adrian Weller S. Swaroop Richard E. Turner FedML 19 12 0 24 Feb 2022
Cyclical Variational Bayes Monte Carlo for Efficient Multi-Modal Posterior Distributions Evaluation F. Igea Alice Cicirello 19 8 0 23 Feb 2022
Approximating Bayes in the 21st Century G. Martin David T. Frazier Christian P. Robert 27 26 0 20 Dec 2021
Information Field Theory and Artificial Intelligence T. Ensslin 19 5 0 19 Dec 2021
Epidemia: An R Package for Semi-Mechanistic Bayesian Modelling of Infectious Diseases using Point Processes Shuhang Tan Axel Gandy Swapnil Mishra Samir Bhatt Seth Flaxman H. Juliette T. Unwin J. Ish-Horowicz 6 9 0 24 Oct 2021
Fitting large mixture models using stochastic component selection Milan Papez Tomás Pevný Václav Smídl 18 0 0 10 Oct 2021
Pathfinder: Parallel quasi-Newton variational inference Lu Zhang Bob Carpenter A. Gelman Aki Vehtari 43 40 0 09 Aug 2021
ADAVI: Automatic Dual Amortized Variational Inference Applied To Pyramidal Bayesian Models Louis Rouillard Demian Wassermann 28 2 0 23 Jun 2021
Geometric variational inference Philipp Frank R. Leike T. Ensslin 14 22 0 21 May 2021
The computational asymptotics of Gaussian variational inference and the Laplace approximation Zuheng Xu Trevor Campbell 19 7 0 13 Apr 2021
Scalable Bayesian computation for crossed and nested hierarchical models O. Papaspiliopoulos Timothée Stumpf-Fétizon Giacomo Zanella 37 10 0 19 Mar 2021
Probabilistic Circuits for Variational Inference in Discrete Graphical Models Andy Shih Stefano Ermon TPM 13 20 0 22 Oct 2020
Privacy-preserving Data Sharing on Vertically Partitioned Data Razane Tajeddine Joonas Jälkö Samuel Kaski Antti Honkela FedML 28 8 0 19 Oct 2020
Tracking disease outbreaks from sparse data with Bayesian inference Bryan Wilder M. Mina Milind Tambe 18 6 0 12 Sep 2020
Naïve regression requires weaker assumptions than factor models to adjust for multiple cause confounding Justin Grimmer D. Knox Brandon M Stewart CML 6 12 0 24 Jul 2020
Stacking for Non-mixing Bayesian Computations: The Curse and Blessing of Multimodal Posteriors Yuling Yao Aki Vehtari Andrew Gelman 29 60 0 22 Jun 2020
Bayesian Neural Networks: An Introduction and Survey Ethan Goan Clinton Fookes BDL UQCV 23 199 0 22 Jun 2020
The role of exchangeability in causal inference O. Saarela D. Stephens E. Moodie 29 5 0 02 Jun 2020
Stochastically Differentiable Probabilistic Programs David Tolpin Yuanshuo Zhou Hongseok Yang BDL 4 0 0 02 Mar 2020
Joint Distributions for TensorFlow Probability Dan Piponi Dave Moore Joshua V. Dillon GP 17 16 0 22 Jan 2020
Approximate Inference for Fully Bayesian Gaussian Process Regression V. Lalchand C. Rasmussen GP 17 51 0 31 Dec 2019