Fixed-Form Variational Posterior Approximation through Stochastic Linear Regression

28 June 2012

Papers citing "Fixed-Form Variational Posterior Approximation through Stochastic Linear Regression"

46 / 46 papers shown

Title
Variational Bayesian Adaptive Learning of Deep Latent Variables for Acoustic Knowledge Transfer Hu Hu Sabato Marco Siniscalchi Chao-Han Huck Yang Chin-Hui Lee 80 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
Particle Semi-Implicit Variational Inference Jen Ning Lim A. M. Johansen 51 4 0 30 Jun 2024
Provably Scalable Black-Box Variational Inference with Structured Variational Families Joohwan Ko Kyurae Kim W. Kim Jacob R. Gardner BDL 33 2 0 19 Jan 2024
Unsupervised Object-Centric Learning from Multiple Unspecified Viewpoints Jinyang Yuan Tonglin Chen Zhimeng Shen Bin Li Xiangyang Xue OCL 33 2 0 03 Jan 2024
Provable convergence guarantees for black-box variational inference Justin Domke Guillaume Garrigos Robert Mansel Gower 18 18 0 04 Jun 2023
The Lie-Group Bayesian Learning Rule E. M. Kıral Thomas Möllenhoff Mohammad Emtiyaz Khan BDL 23 2 0 08 Mar 2023
Bayesian Learning for Neural Networks: an algorithmic survey M. Magris Alexandros Iosifidis BDL DRL 35 68 0 21 Nov 2022
SIXO: Smoothing Inference with Twisted Objectives Dieterich Lawson Allan Raventós Andrew Warrington Scott W. Linderman BDL 13 15 0 13 Jun 2022
MixFlows: principled variational inference via mixed flows Zuheng Xu Na Chen Trevor Campbell 55 8 0 16 May 2022
Partitioned Variational Inference: A Framework for Probabilistic Federated Learning Matthew Ashman T. Bui Cuong V Nguyen Efstratios Markou Adrian Weller S. Swaroop Richard Turner FedML 19 12 0 24 Feb 2022
A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine Learning Iris A. M. Huijben W. Kool Max B. Paulus Ruud J. G. van Sloun 28 93 0 04 Oct 2021
The Bayesian Learning Rule Mohammad Emtiyaz Khan Håvard Rue BDL 63 73 0 09 Jul 2021
Variational Variance: Simple, Reliable, Calibrated Heteroscedastic Noise Variance Parameterization Andrew Stirn David A. Knowles DRL 15 10 0 08 Jun 2020
The role of exchangeability in causal inference O. Saarela D. Stephens E. Moodie 36 5 0 02 Jun 2020
Markovian Score Climbing: Variational Inference with KL(p\|\|q) C. A. Naesseth Fredrik Lindsten David M. Blei 121 54 0 23 Mar 2020
Adversarial Attacks on Probabilistic Autoregressive Forecasting Models Raphaël Dang-Nhu Gagandeep Singh Pavol Bielik Martin Vechev AI4TS AAML 39 20 0 08 Mar 2020
Inverse Graphics GAN: Learning to Generate 3D Shapes from Unstructured 2D Data Sebastian Lunz Yingzhen Li Andrew Fitzgibbon Nate Kushman 3DV GAN 17 54 0 28 Feb 2020
Handling the Positive-Definite Constraint in the Bayesian Learning Rule Wu Lin Mark W. Schmidt Mohammad Emtiyaz Khan BDL 37 35 0 24 Feb 2020
Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights Theofanis Karaletsos T. Bui BDL 17 23 0 10 Feb 2020
A Recurrent Variational Autoencoder for Speech Enhancement Simon Leglaive Xavier Alameda-Pineda Laurent Girin Radu Horaud DRL 12 78 0 24 Oct 2019
Nonasymptotic estimates for Stochastic Gradient Langevin Dynamics under local conditions in nonconvex optimization Ying Zhang Ömer Deniz Akyildiz Theodoros Damoulas Sotirios Sabanis 11 44 0 04 Oct 2019
Monte Carlo Gradient Estimation in Machine Learning S. Mohamed Mihaela Rosca Michael Figurnov A. Mnih 45 397 0 25 Jun 2019
Scalable Bayesian dynamic covariance modeling with variational Wishart and inverse Wishart processes Creighton Heaukulani Mark van der Wilk BDL 29 15 0 22 Jun 2019
Encoding prior knowledge in the structure of the likelihood Jakob Knollmüller T. Ensslin 36 11 0 11 Dec 2018
Partitioned Variational Inference: A unified framework encompassing federated and continual learning T. Bui Cuong V Nguyen S. Swaroop Richard Turner FedML 24 55 0 27 Nov 2018
Fast yet Simple Natural-Gradient Descent for Variational Inference in Complex Models Mohammad Emtiyaz Khan Didrik Nielsen BDL 34 62 0 12 Jul 2018
Pathwise Derivatives Beyond the Reparameterization Trick M. Jankowiak F. Obermeyer 30 110 0 05 Jun 2018
Semi-Implicit Variational Inference Mingzhang Yin Mingyuan Zhou BDL 35 121 0 28 May 2018
Gaussian variational approximation for high-dimensional state space models M. Quiroz David J. Nott Robert Kohn 24 40 0 24 Jan 2018
Advances in Variational Inference Cheng Zhang Judith Butepage Hedvig Kjellström Stephan Mandt BDL 38 684 0 15 Nov 2017
Variational Continual Learning Cuong V Nguyen Yingzhen Li T. Bui Richard Turner CLL VLM BDL 36 728 0 29 Oct 2017
Reparameterizing the Birkhoff Polytope for Variational Permutation Inference Scott W. Linderman Gonzalo E. Mena H. Cooper Liam Paninski John P. Cunningham 18 50 0 26 Oct 2017
Multiplicative Normalizing Flows for Variational Bayesian Neural Networks Christos Louizos Max Welling BDL 21 454 0 06 Mar 2017
Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms C. A. Naesseth Francisco J. R. Ruiz Scott W. Linderman David M. Blei BDL 25 107 0 18 Oct 2016
Gaussian variational approximation with sparse precision matrices Linda S. L. Tan David J. Nott 30 76 0 18 May 2016
Overdispersed Black-Box Variational Inference Francisco J. R. Ruiz Michalis K. Titsias David M. Blei 22 47 0 03 Mar 2016
Black-box $α$ -divergence Minimization José Miguel Hernández-Lobato Yingzhen Li Mark Rowland Daniel Hernández-Lobato T. Bui Richard Turner 21 137 0 10 Nov 2015
Hierarchical Variational Models Rajesh Ranganath Dustin Tran David M. Blei DRL VLM 14 335 0 07 Nov 2015
Faster Stochastic Variational Inference using Proximal-Gradient Methods with General Divergence Functions Mohammad Emtiyaz Khan Reza Babanezhad Wu Lin Mark W. Schmidt Masashi Sugiyama 28 49 0 31 Oct 2015
Stochastic gradient variational Bayes for gamma approximating distributions David A. Knowles BDL 14 50 0 04 Sep 2015
Correlated Random Measures Rajesh Ranganath David M. Blei 22 21 0 02 Jul 2015
Copula variational inference Dustin Tran David M. Blei E. Airoldi 18 5 0 10 Jun 2015
Variational Dropout and the Local Reparameterization Trick Diederik P. Kingma Tim Salimans Max Welling BDL 49 1,493 0 08 Jun 2015
Diversifying Sparsity Using Variational Determinantal Point Processes N. Batmanghelich G. Quon Alex Kulesza Manolis Kellis Polina Golland L. Bornn 25 14 0 23 Nov 2014
Structured Stochastic Variational Inference Matthew D. Hoffman David M. Blei BDL 26 87 0 16 Apr 2014