Stochastic Variational Inference

29 June 2012

Matt Hoffman

Papers citing "Stochastic Variational Inference"

50 / 1,065 papers shown

Title
Identification, Interpretability, and Bayesian Word Embeddings Adam M. Lauretig BDL 20 11 0 02 Apr 2019
Perturbative estimation of stochastic gradients L. Ambrogioni Marcel van Gerven 12 0 0 31 Mar 2019
Laplace Landmark Localization Joseph P. Robinson Yuncheng Li Ning Zhang Y. Fu Sergey Tulyakov CVBM 22 43 0 27 Mar 2019
Cyclical Annealing Schedule: A Simple Approach to Mitigating KL Vanishing Hao Fu Chunyuan Li Xiaodong Liu Jianfeng Gao Asli Celikyilmaz Lawrence Carin ODL 27 361 0 25 Mar 2019
Deep Gaussian Processes for Multi-fidelity Modeling Kurt Cutajar Mark Pullin Andreas C. Damianou Neil D. Lawrence Javier I. González AI4CE 30 109 0 18 Mar 2019
Applying Probabilistic Programming to Affective Computing Desmond C. Ong Harold Soh Jamil Zaki Noah D. Goodman 27 20 0 15 Mar 2019
Likelihood-free MCMC with Amortized Approximate Ratio Estimators Joeri Hermans Volodimir Begy Gilles Louppe 32 20 0 10 Mar 2019
The Variational Predictive Natural Gradient Da Tang Rajesh Ranganath BDL DRL 16 8 0 07 Mar 2019
LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models Yuanshuo Zhou Bradley Gram-Hansen Tobias Kohn Tom Rainforth Hongseok Yang Frank Wood 36 24 0 06 Mar 2019
Deep active subspaces - a scalable method for high-dimensional uncertainty propagation Rohit Tripathy Ilias Bilionis 25 12 0 27 Feb 2019
Training Variational Autoencoders with Buffered Stochastic Variational Inference Rui Shu Hung Bui Jay Whang Stefano Ermon BDL 11 3 0 27 Feb 2019
Bayesian Image Classification with Deep Convolutional Gaussian Processes Vincent Dutordoir Mark van der Wilk A. Artemev J. Hensman UQCV BDL 30 32 0 15 Feb 2019
Gaussian Mean Field Regularizes by Limiting Learned Information Julius Kunze Louis Kirsch H. Ritter David Barber FedML MLT 11 2 0 12 Feb 2019
A physics-aware, probabilistic machine learning framework for coarse-graining high-dimensional systems in the Small Data regime Constantin Grigo P. Koutsourelakis AI4CE 21 25 0 11 Feb 2019
Manifold Optimization Assisted Gaussian Variational Approximation Bingxin Zhou Junbin Gao Minh-Ngoc Tran Richard Gerlach 19 6 0 11 Feb 2019
Radial and Directional Posteriors for Bayesian Neural Networks Changyong Oh Kamil Adamczewski Mijung Park BDL 31 20 0 07 Feb 2019
BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling Lars Maaløe Marco Fraccaro Valentin Liévin Ole Winther BDL DRL 24 213 0 06 Feb 2019
Total stochastic gradient algorithms and applications in reinforcement learning Paavo Parmas 28 17 0 05 Feb 2019
Particle Flow Bayes' Rule Xinshi Chen H. Dai Le Song 22 9 0 02 Feb 2019
Intelligent architectures for robotics: The merging of cognition and emotion L. Pessoa 6 17 0 01 Feb 2019
Kernel embedded nonlinear observational mappings in the variational mapping particle filter M. Pulido P. Leeuwen D. Posselt 29 7 0 29 Jan 2019
Learning Global Pairwise Interactions with Bayesian Neural Networks Tianyu Cui Pekka Marttinen Samuel Kaski BDL 18 17 0 24 Jan 2019
Disentangling Video with Independent Prediction William F. Whitney Rob Fergus CML CoGe OCL DRL 43 1 0 17 Jan 2019
Lagging Inference Networks and Posterior Collapse in Variational Autoencoders Junxian He Daniel M. Spokoyny Graham Neubig Taylor Berg-Kirkpatrick BDL DRL 25 272 0 16 Jan 2019
Large-Scale Joint Topic, Sentiment & User Preference Analysis for Online Reviews Xinli Yu Zheng Chen Wei-Shih Yang Xiaohua Hu E. Yan BDL 6 3 0 14 Jan 2019
Learning Nonlinear State Space Models with Hamiltonian Sequential Monte Carlo Sampler Duo Xu 29 2 0 03 Jan 2019
Adversarial Learning of a Sampler Based on an Unnormalized Distribution Chunyuan Li Ke Bai Jianqiao Li Guoyin Wang Changyou Chen Lawrence Carin 16 10 0 03 Jan 2019
A Full Probabilistic Model for Yes/No Type Crowdsourcing in Multi-Class Classification Belen Saldias-Fuentes P. Protopapas K. Pichara 12 0 0 02 Jan 2019
Mixed Membership Recurrent Neural Networks G. Fazelnia Mark Ibrahim C. Modarres K. Wu John Paisley 116 1 0 23 Dec 2018
Disentangling Latent Space for VAE by Label Relevant/Irrelevant Dimensions Zhilin Zheng Li Sun CML CoGe DRL 18 46 0 22 Dec 2018
A Factorial Mixture Prior for Compositional Deep Generative Models Ulrich Paquet Sumedh Ghaisas O. Tieleman CoGe 12 1 0 18 Dec 2018
Bayesian Mean-parameterized Nonnegative Binary Matrix Factorization Alberto Lumbreras Louis Filstroff Cédric Févotte 20 15 0 17 Dec 2018
A Tutorial on Deep Latent Variable Models of Natural Language Yoon Kim Sam Wiseman Alexander M. Rush BDL VLM 30 42 0 17 Dec 2018
Latent Dirichlet Allocation in Generative Adversarial Networks Lili Pan Shen Cheng Jian-Dong Liu Yazhou Ren Zenglin Xu GAN 16 3 0 17 Dec 2018
Neural Processes Mixed-Effect Models for Deep Normative Modeling of Clinical Neuroimaging Data S. M. Kia A. Marquand 24 25 0 12 Dec 2018
KF-LAX: Kronecker-factored curvature estimation for control variate optimization in reinforcement learning Mohammad Firouzi 19 0 0 11 Dec 2018
Uncertainty propagation in neural networks for sparse coding Danil Kuzin Olga Isupova Lyudmila Mihaylova BDL UQCV 14 0 0 29 Nov 2018
Bayesian Adversarial Spheres: Bayesian Inference and Adversarial Examples in a Noiseless Setting Artur Bekasov Iain Murray AAML BDL 20 14 0 29 Nov 2018
Autoconj: Recognizing and Exploiting Conjugacy Without a Domain-Specific Language Matthew D. Hoffman Matthew J. Johnson Dustin Tran 6 17 0 29 Nov 2018
Partitioned Variational Inference: A unified framework encompassing federated and continual learning T. Bui Cuong V Nguyen S. Swaroop Richard Turner FedML 27 55 0 27 Nov 2018
Joint Mapping and Calibration via Differentiable Sensor Fusion Jonathan P. Chen F. Obermeyer V. Lyapunov L. Gueguen Noah D. Goodman 26 0 0 21 Nov 2018
A General Method for Amortizing Variational Filtering Joseph Marino Milan Cvitkovic Yisong Yue 27 34 0 13 Nov 2018
On the Performance and Convergence of Distributed Stream Processing via Approximate Fault Tolerance Zhinan Cheng Qun Huang P. Lee 11 8 0 12 Nov 2018
SLANG: Fast Structured Covariance Approximations for Bayesian Deep Learning with Natural Gradient Aaron Mishkin Frederik Kunstner Didrik Nielsen Mark Schmidt Mohammad Emtiyaz Khan BDL UQCV 22 59 0 11 Nov 2018
Adapting multi-armed bandits policies to contextual bandits scenarios David Cortes 27 32 0 11 Nov 2018
Deep Ensemble Bayesian Active Learning : Addressing the Mode Collapse issue in Monte Carlo dropout via Ensembles Remus Pop Patric Fulop UQCV 27 41 0 09 Nov 2018
Wasserstein variational gradient descent: From semi-discrete optimal transport to ensemble variational inference L. Ambrogioni Rémi Flamary R. Tavenard OT 14 12 0 07 Nov 2018
DAPPER: Scaling Dynamic Author Persona Topic Model to Billion Word Corpora S. Zee Alice Havrileck 17 3 0 03 Nov 2018
Understanding and Comparing Scalable Gaussian Process Regression for Big Data Haitao Liu Jianfei Cai Yew-Soon Ong Yi Wang 27 24 0 03 Nov 2018
Dirichlet belief networks for topic structure learning He Zhao Lan Du Wray Buntine Mingyuan Zhou OOD BDL 26 42 0 02 Nov 2018