Stochastic Variational Inference

29 June 2012

Matt Hoffman

Papers citing "Stochastic Variational Inference"

50 / 1,065 papers shown

Title
Stochastic Variational Inference via Upper Bound Chunlin Ji Haige Shen UQCV BDL 24 11 0 02 Dec 2019
Transflow Learning: Repurposing Flow Models Without Retraining Andrew Gambardella A. G. Baydin Philip Torr DRL AI4CE 14 8 0 29 Nov 2019
Interactive Text Ranking with Bayesian Optimisation: A Case Study on Community QA and Summarisation Edwin Simpson Yang Gao Iryna Gurevych BDL 21 10 0 22 Nov 2019
Modeling emotion in complex stories: the Stanford Emotional Narratives Dataset Desmond C. Ong Zhengxuan Wu Zhi-Xuan Tan Marianne C. Reddan Isabella Kahhale Alison Mattek Jamil Zaki AI4TS 17 57 0 22 Nov 2019
Language Model-Driven Unsupervised Neural Machine Translation Wei Zhang Y. Lin Ruoran Ren Xiaodong Wang Zhenshuang Liang Zhen Huang 12 0 0 10 Nov 2019
Exactly Sparse Gaussian Variational Inference with Application to Derivative-Free Batch Nonlinear State Estimation T. Barfoot James Richard Forbes David J. Yoon 28 39 0 09 Nov 2019
Auto-encoding brain networks with applications to analyzing large-scale brain imaging datasets Meimei Liu Zhengwu Zhang David B. Dunson 21 4 0 07 Nov 2019
Integrating Markov processes with structural causal modeling enables counterfactual inference in complex systems Robert Osazuwa Ness Kaushal Paneri O. Vitek 25 7 0 06 Nov 2019
Scalable Variational Gaussian Processes for Crowdsourcing: Glitch Detection in LIGO Pablo Morales-Álvarez Pablo Ruiz S. Coughlin Rafael Molina Aggelos K. Katsaggelos 21 14 0 05 Nov 2019
Statistical Inference in Mean-Field Variational Bayes Wei Han Yun Yang 28 17 0 04 Nov 2019
Review: Ordinary Differential Equations For Deep Learning Xinshi Chen AI4TS AI4CE 33 5 0 01 Nov 2019
Continual Multi-task Gaussian Processes P. Moreno-Muñoz A. Artés-Rodríguez Mauricio A. Alvarez 14 13 0 31 Oct 2019
Inverse Graphics: Unsupervised Learning of 3D Shapes from Single Images Talip Uçar 36 0 0 31 Oct 2019
Divide, Conquer, and Combine: a New Inference Strategy for Probabilistic Programs with Stochastic Support Yuanshuo Zhou Hongseok Yang Yee Whye Teh Tom Rainforth TPM 29 19 0 29 Oct 2019
Online Gaussian LDA for Unsupervised Pattern Mining from Utility Usage Data S. Mohamad A. Bouchachia 9 8 0 25 Oct 2019
A Recurrent Variational Autoencoder for Speech Enhancement Simon Leglaive Xavier Alameda-Pineda Laurent Girin Radu Horaud DRL 22 78 0 24 Oct 2019
Optimistic Distributionally Robust Optimization for Nonparametric Likelihood Approximation Viet Anh Nguyen Soroosh Shafieezadeh-Abadeh Man-Chung Yue Daniel Kuhn W. Wiesemann 19 29 0 23 Oct 2019
Parametric Gaussian Process Regressors M. Jankowiak Geoffrey Pleiss Jacob R. Gardner UQCV 39 5 0 16 Oct 2019
The Renyi Gaussian Process: Towards Improved Generalization Xubo Yue Raed Al Kontar 109 3 0 15 Oct 2019
A unified view of likelihood ratio and reparameterization gradients and an optimal importance sampling scheme Paavo Parmas Masashi Sugiyama 19 3 0 14 Oct 2019
Introducing an Explicit Symplectic Integration Scheme for Riemannian Manifold Hamiltonian Monte Carlo Adam D. Cobb A. G. Baydin Andrew Markham Stephen J. Roberts 24 32 0 14 Oct 2019
Distributed Computation for Marginal Likelihood based Model Choice Alexander K. Buchholz Daniel Ahfock S. Richardson FedML 25 5 0 10 Oct 2019
Increasing Expressivity of a Hyperspherical VAE Tim R. Davidson Jakub M. Tomczak E. Gavves 13 6 0 07 Oct 2019
Tightening Bounds for Variational Inference by Revisiting Perturbation Theory Robert Bamler Cheng Zhang Manfred Opper Stephan Mandt 22 3 0 30 Sep 2019
The $f$ -Divergence Expectation Iteration Scheme Kamélia Daudel Randal Douc Franccois Portier François Roueff 22 1 0 26 Sep 2019
Scalable Gaussian Process Classification with Additive Noise for Various Likelihoods Haitao Liu Yew-Soon Ong Ziwei Yu Jianfei Cai Xiaobo Shen 21 3 0 14 Sep 2019
Mutual-Information Regularization in Markov Decision Processes and Actor-Critic Learning Felix Leibfried Jordi Grau-Moya 15 21 0 11 Sep 2019
Neural Gaussian Copula for Variational Autoencoder P. Wang William Yang Wang BDL DRL 11 13 0 09 Sep 2019
Dissecting Non-Vacuous Generalization Bounds based on the Mean-Field Approximation Konstantinos Pitas 19 8 0 06 Sep 2019
Meta Learning with Relational Information for Short Sequences Yujia Xie Haoming Jiang Feng Liu T. Zhao H. Zha 25 14 0 04 Sep 2019
Latent Gaussian process with composite likelihoods and numerical quadrature S. Ramchandran Miika Koskinen Harri Lähdesmäki 13 0 0 04 Sep 2019
ForkNet: Multi-branch Volumetric Semantic Completion from a Single Depth Image Yida Wang D. Tan Nassir Navab Federico Tombari 3DV 3DPC 25 56 0 03 Sep 2019
Learning Latent Parameters without Human Response Patterns: Item Response Theory with Artificial Crowds John P. Lalor Hao Wu Hong-ye Yu 18 42 0 29 Aug 2019
A Probabilistic Representation of Deep Learning Xinjie Lan Kenneth Barner UQCV BDL AI4CE 19 1 0 26 Aug 2019
Bayesian Generative Models for Knowledge Transfer in MRI Semantic Segmentation Problems Anna Kuzina Evgenii Egorov Evgeny Burnaev MedIm 31 19 0 15 Aug 2019
Convergence Rates of Variational Inference in Sparse Deep Learning Badr-Eddine Chérief-Abdellatif BDL 14 38 0 09 Aug 2019
Probabilistic Models with Deep Neural Networks A. Masegosa Rafael Cabañas H. Langseth Thomas D. Nielsen Antonio Salmerón BDL 16 12 0 09 Aug 2019
Variational Bayes on Manifolds Minh-Ngoc Tran D. Nguyen Duy Nguyen 11 23 0 08 Aug 2019
Population Predictive Checks Rajesh Ranganath David M. Blei Rajesh Ranganath 9 12 0 02 Aug 2019
Updating Variational Bayes: Fast sequential posterior inference Nathaniel Tomasetti Catherine S. Forbes Anastasios Panagiotelis 20 9 0 01 Aug 2019
A Theoretical Case Study of Structured Variational Inference for Community Detection Mingzhang Yin Y. X. R. Wang Purnamrita Sarkar 16 8 0 29 Jul 2019
Towards Verified Stochastic Variational Inference for Probabilistic Programs Wonyeol Lee Hangyeol Yu Xavier Rival Hongseok Yang 24 23 0 20 Jul 2019
Kernel Mode Decomposition and programmable/interpretable regression networks H. Owhadi C. Scovel G. Yoo 21 5 0 19 Jul 2019
Amortized Monte Carlo Integration Adam Goliñski Frank Wood Tom Rainforth 36 4 0 18 Jul 2019
Subspace Inference for Bayesian Deep Learning Pavel Izmailov Wesley J. Maddox Polina Kirichenko T. Garipov Dmitry Vetrov A. Wilson UQCV BDL 38 143 0 17 Jul 2019
Structured Variational Inference in Unstable Gaussian Process State Space Models Silvan Melchior Sebastian Curi Felix Berkenkamp Andreas Krause 25 4 0 16 Jul 2019
The Dynamic Embedded Topic Model Adji Bousso Dieng Francisco J. R. Ruiz David M. Blei BDL 23 87 0 12 Jul 2019
Trust-Region Variational Inference with Gaussian Mixture Models Oleg Arenz Mingjun Zhong Gerhard Neumann 37 18 0 10 Jul 2019
Deep Active Inference as Variational Policy Gradients Beren Millidge BDL 32 103 0 08 Jul 2019
Bayesian deep learning with hierarchical prior: Predictions from limited and noisy data Xihaier Luo A. Kareem BDL UQCV 11 28 0 08 Jul 2019