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Variational Inference: A Review for Statisticians

4 January 2016

Papers citing "Variational Inference: A Review for Statisticians"

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Title
Deep Bayesian Active Learning for Multiple Correct Outputs Khaled Jedoui Ranjay Krishna Michael S. Bernstein Li Fei-Fei BDL OOD UQCV 93 14 0 02 Dec 2019
A probabilistic assessment of the Indo-Aryan Inner-Outer Hypothesis C. Cathcart 56 15 0 29 Nov 2019
Label Dependent Deep Variational Paraphrase Generation Siamak Shakeri A. Sethy BDL DRL 15 6 0 27 Nov 2019
Neural Latent Space Model for Dynamic Networks and Temporal Knowledge Graphs Tony Gracious Shubham Gupta Arun Kanthali Rui M. Castro Ambedkar Dukkipati BDL 120 0 0 26 Nov 2019
Representation Learning: A Statistical Perspective Jianwen Xie Ruiqi Gao Erik Nijkamp Song-Chun Zhu Ying Nian Wu SSL 49 12 0 26 Nov 2019
Scaling active inference Alexander Tschantz Manuel Baltieri A. Seth Christopher L. Buckley BDL AI4CE 73 69 0 24 Nov 2019
A Fully Natural Gradient Scheme for Improving Inference of the Heterogeneous Multi-Output Gaussian Process Model Juan J. Giraldo Mauricio A. Alvarez BDL 119 5 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 67 59 0 22 Nov 2019
Estimating uncertainty of earthquake rupture using Bayesian neural network S. Ahamed Md Mesbah Uddin 33 5 0 21 Nov 2019
Assessment and adjustment of approximate inference algorithms using the law of total variance Xue Yu David J. Nott Minh-Ngoc Tran Nadja Klein 65 15 0 20 Nov 2019
Fuzzy Tiling Activations: A Simple Approach to Learning Sparse Representations Online Yangchen Pan Kirby Banman Martha White 42 0 0 19 Nov 2019
Implicit Generative Modeling for Efficient Exploration Neale Ratzlaff Qinxun Bai Fuxin Li Wenyuan Xu 70 12 0 19 Nov 2019
Scalable and Accurate Variational Bayes for High-Dimensional Binary Regression Models A. Fasano Daniele Durante Giacomo Zanella 99 32 0 15 Nov 2019
Equipping SBMs with RBMs: An Explainable Approach for Analysis of Networks with Covariates Shubham Gupta Gururaj K. Ambedkar Dukkipati Rui M. Castro 32 1 0 11 Nov 2019
Don't Blame the ELBO! A Linear VAE Perspective on Posterior Collapse James Lucas George Tucker Roger C. Grosse Mohammad Norouzi CoGe DRL 92 180 0 06 Nov 2019
An Information Theory Approach on Deciding Spectroscopic Follow Ups Javiera Astudillo P. Protopapas K. Pichara P. Huijse 32 4 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 45 14 0 05 Nov 2019
A Latent Topic Model with Markovian Transition for Process Data Haochen Xu Guanhua Fang Z. Ying 31 7 0 05 Nov 2019
Statistical Inference in Mean-Field Variational Bayes Wei Han Yun Yang 48 18 0 04 Nov 2019
Mean-field inference methods for neural networks Marylou Gabrié AI4CE 127 33 0 03 Nov 2019
Variational Bayesian inference of hidden stochastic processes with unknown parameters Komlan Atitey P. Loskot Lyudmila Mihaylova 30 0 0 02 Nov 2019
Learning Hawkes Processes from a Handful of Events Farnood Salehi W. Trouleau Matthias Grossglauser Patrick Thiran BDL CML 131 37 0 01 Nov 2019
Energy-Inspired Models: Learning with Sampler-Induced Distributions Dieterich Lawson George Tucker Bo Dai Rajesh Ranganath 92 31 0 31 Oct 2019
Thompson Sampling via Local Uncertainty Zhendong Wang Mingyuan Zhou 80 19 0 30 Oct 2019
Spectral Subsampling MCMC for Stationary Time Series R. Salomone M. Quiroz Robert Kohn M. Villani Minh-Ngoc Tran AI4TS 78 15 0 30 Oct 2019
Neural Density Estimation and Likelihood-free Inference George Papamakarios BDL DRL 100 47 0 29 Oct 2019
Semi-Implicit Stochastic Recurrent Neural Networks Ehsan Hajiramezanali Arman Hasanzadeh N. Duffield Krishna R. Narayanan Mingyuan Zhou Xiaoning Qian BDL 58 5 0 28 Oct 2019
Stein Variational Gradient Descent With Matrix-Valued Kernels Dilin Wang Ziyang Tang Minh Nguyen Qiang Liu 90 62 0 28 Oct 2019
On the Global Convergence of (Fast) Incremental Expectation Maximization Methods Belhal Karimi Hoi-To Wai Eric Moulines M. Lavielle 74 28 0 28 Oct 2019
A Recurrent Variational Autoencoder for Speech Enhancement Simon Leglaive Xavier Alameda-Pineda Laurent Girin Radu Horaud DRL 147 80 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 69 29 0 23 Oct 2019
Collapsed Amortized Variational Inference for Switching Nonlinear Dynamical Systems Zhe Dong Bryan Seybold Kevin Patrick Murphy Hung Bui BDL 86 32 0 21 Oct 2019
Maximum Probability Theorem: A Framework for Probabilistic Learning Amir Emad Marvasti Ehsan Emad Marvasti Ulas Bagci H. Foroosh 31 1 0 21 Oct 2019
Scaling up Psychology via Scientific Regret Minimization: A Case Study in Moral Decisions Mayank Agrawal Joshua C. Peterson Thomas Griffiths 35 1 0 16 Oct 2019
The Renyi Gaussian Process: Towards Improved Generalization Xubo Yue Raed Al Kontar 140 3 0 15 Oct 2019
Challenges in Markov chain Monte Carlo for Bayesian neural networks Theodore Papamarkou Jacob D. Hinkle M. T. Young D. Womble BDL 131 51 0 15 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 62 32 0 14 Oct 2019
Deep Kernels with Probabilistic Embeddings for Small-Data Learning Ankur Mallick Chaitanya Dwivedi B. Kailkhura Gauri Joshi T. Y. Han BDL UQCV 51 8 0 13 Oct 2019
Prescribed Generative Adversarial Networks Adji Bousso Dieng Francisco J. R. Ruiz David M. Blei Michalis K. Titsias GAN DRL 80 62 0 09 Oct 2019
Validated Variational Inference via Practical Posterior Error Bounds Jonathan H. Huggins Mikolaj Kasprzak Trevor Campbell Tamara Broderick 90 37 0 09 Oct 2019
Stochastic triangular mesh mapping: A terrain mapping technique for autonomous mobile robots C. Dufauret Lombard C. E. V. Daalen 3DV 115 5 0 08 Oct 2019
Streamlined Variational Inference for Linear Mixed Models with Crossed Random Effects M. Menictas Gioia Di Credico M. Wand 119 11 0 04 Oct 2019
CWAE-IRL: Formulating a supervised approach to Inverse Reinforcement Learning problem Arpan Kusari BDL 22 0 0 02 Oct 2019
The Neural Moving Average Model for Scalable Variational Inference of State Space Models Tom Ryder D. Prangle Andrew Golightly Isaac Matthews BDL AI4TS 92 6 0 02 Oct 2019
Action Anticipation for Collaborative Environments: The Impact of Contextual Information and Uncertainty-Based Prediction Clebeson Canuto dos Santos Plinio Moreno J. L. A. Samatelo R. Vassallo J. Santos-Victor 68 7 0 01 Oct 2019
Tightening Bounds for Variational Inference by Revisiting Perturbation Theory Robert Bamler Cheng Zhang Manfred Opper Stephan Mandt 48 3 0 30 Sep 2019
Improving Textual Network Learning with Variational Homophilic Embeddings Wenlin Wang Chenyang Tao Zhe Gan Guoyin Wang Liqun Chen Xinyuan Zhang Ruiyi Zhang Qian Yang Ricardo Henao Lawrence Carin DRL 39 16 0 30 Sep 2019
The $f$ -Divergence Expectation Iteration Scheme Kamélia Daudel Randal Douc Franccois Portier François Roueff 97 1 0 26 Sep 2019
Active inference: demystified and compared Noor Sajid Philip J. Ball Thomas Parr Karl J. Friston OffRL 41 3 0 24 Sep 2019
A Theory of Uncertainty Variables for State Estimation and Inference Rajat Talak S. Karaman E. Modiano 52 1 0 24 Sep 2019