Variational Inference: A Review for Statisticians

4 January 2016

Papers citing "Variational Inference: A Review for Statisticians"

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Title
Uncertainty Quantification on Graph Learning: A Survey Chao Chen Chenghua Guo Rui Xu Xiangwen Liao Xi Zhang Sihong Xie Hui Xiong Mohit Bansal AI4CE 37 1 0 23 Apr 2024
Physics-integrated generative modeling using attentive planar normalizing flow based variational autoencoder Sheikh Waqas Akhtar DRL 25 0 0 18 Apr 2024
Analytical Approximation of the ELBO Gradient in the Context of the Clutter Problem Roumen Nikolaev Popov 29 0 0 16 Apr 2024
Dynamic fault detection and diagnosis of industrial alkaline water electrolyzer process with variational Bayesian dictionary learning Qi Zhang Lei Xie Wei Xu Hongye Su 18 4 0 15 Apr 2024
Convergence of coordinate ascent variational inference for log-concave measures via optimal transport Manuel Arnese Daniel Lacker 29 6 0 12 Apr 2024
Polynomial-time derivation of optimal k-tree topology from Markov networks Fereshteh R. Dastjerdi Liming Cai 11 0 0 09 Apr 2024
Dynamic Conditional Optimal Transport through Simulation-Free Flows Gavin Kerrigan Giosue Migliorini Padhraic Smyth OT 38 10 0 05 Apr 2024
Bi-level Guided Diffusion Models for Zero-Shot Medical Imaging Inverse Problems Hossein Askari Fred Roosta Hongfu Sun MedIm DiffM 38 3 0 04 Apr 2024
CLaM-TTS: Improving Neural Codec Language Model for Zero-Shot Text-to-Speech Jaehyeon Kim Keon Lee Seungjun Chung Jaewoong Cho 74 39 0 03 Apr 2024
Conditional Pseudo-Reversible Normalizing Flow for Surrogate Modeling in Quantifying Uncertainty Propagation Minglei Yang Pengjun Wang Ming Fan Dan Lu Yanzhao Cao Guannan Zhang AI4CE 27 1 0 31 Mar 2024
Causal Inference for Human-Language Model Collaboration Bohan Zhang Yixin Wang Paramveer S. Dhillon 38 2 0 30 Mar 2024
Uncertainty-Aware SAR ATR: Defending Against Adversarial Attacks via Bayesian Neural Networks Tian Ye Rajgopal Kannan Viktor Prasanna Carl E. Busart AAML 16 1 0 27 Mar 2024
Neural Multimodal Topic Modeling: A Comprehensive Evaluation Felipe González-Pizarro Giuseppe Carenini VGen 45 1 0 26 Mar 2024
Bridging the Sim-to-Real Gap with Bayesian Inference Jonas Rothfuss Bhavya Sukhija Lenart Treven Florian Dorfler Stelian Coros Andreas Krause AI4CE 41 3 0 25 Mar 2024
Federated Bayesian Deep Learning: The Application of Statistical Aggregation Methods to Bayesian Models John Fischer Marko Orescanin Justin Loomis Patrick McClure FedML 51 3 0 22 Mar 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
Predictive, scalable and interpretable knowledge tracing on structured domains Hanqi Zhou Robert Bamler Charley M. Wu Álvaro Tejero-Cantero AI4Ed 20 7 0 19 Mar 2024
Function-space Parameterization of Neural Networks for Sequential Learning Aidan Scannell Riccardo Mereu Paul E. Chang Ella Tamir Joni Pajarinen Arno Solin BDL 34 5 0 16 Mar 2024
Sequential Monte Carlo for Inclusive KL Minimization in Amortized Variational Inference Declan McNamara J. Loper Jeffrey Regier BDL 39 2 0 15 Mar 2024
Disentangling shared and private latent factors in multimodal Variational Autoencoders Kaspar Märtens Christopher Yau DRL 11 0 0 10 Mar 2024
Nonparametric Automatic Differentiation Variational Inference with Spline Approximation Yuda Shao Shan Yu Tianshu Feng 34 1 0 10 Mar 2024
Variational Inference of Parameters in Opinion Dynamics Models Jacopo Lenti Fabrizio Silvestri G. D. F. Morales 31 3 0 08 Mar 2024
Uncertainty quantification for deeponets with ensemble kalman inversion Andrew Pensoneault Xueyu Zhu 26 1 0 06 Mar 2024
CoRMF: Criticality-Ordered Recurrent Mean Field Ising Solver Zhenyu Pan Ammar Gilani En-Jui Kuo Zhuo Liu LRM 43 4 0 05 Mar 2024
Bayesian Uncertainty Estimation by Hamiltonian Monte Carlo: Applications to Cardiac MRI Segmentation Yidong Zhao João Tourais Iain Pierce Christian Nitsche T. Treibel Sebastian Weingartner Artur M. Schweidtmann Qian Tao BDL UQCV 43 5 0 04 Mar 2024
Feint in Multi-Player Games Junyu Liu Wangkai Jin Xiangjun Peng OffRL 25 0 0 04 Mar 2024
Learning with Logical Constraints but without Shortcut Satisfaction Zenan Li Zehua Liu Yuan Yao Jingwei Xu Taolue Chen Xiaoxing Ma Jian Lu NAI 30 18 0 01 Mar 2024
On Cyclical MCMC Sampling Liwei Wang Xinru Liu Aaron Smith Aguemon Y. Atchadé 30 1 0 01 Mar 2024
Sparse Variational Contaminated Noise Gaussian Process Regression with Applications in Geomagnetic Perturbations Forecasting Daniel Iong Matthew McAnear Yuezhou Qu S. Zou Gabor Toth Yang Chen 16 0 0 27 Feb 2024
Material Microstructure Design Using VAE-Regression with Multimodal Prior Avadhut Sardeshmukh Sreedhar Reddy B. Gautham Pushpak Bhattacharyya 19 0 0 27 Feb 2024
Stable Training of Normalizing Flows for High-dimensional Variational Inference Daniel Andrade BDL TPM 43 1 0 26 Feb 2024
Accelerating Convergence of Stein Variational Gradient Descent via Deep Unfolding Yuya Kawamura Satoshi Takabe BDL 34 0 0 23 Feb 2024
Batch and match: black-box variational inference with a score-based divergence Diana Cai Chirag Modi Loucas Pillaud-Vivien C. Margossian Robert Mansel Gower David M. Blei Lawrence K. Saul 38 9 0 22 Feb 2024
Composite likelihood inference for the Poisson log-normal model Julien Stoehr Stephane S. Robin 18 3 0 22 Feb 2024
Bayesian Neural Networks with Domain Knowledge Priors Dylan Sam Rattana Pukdee Daniel P. Jeong Yewon Byun J. Zico Kolter BDL UQCV 38 9 0 20 Feb 2024
Diagonalisation SGD: Fast & Convergent SGD for Non-Differentiable Models via Reparameterisation and Smoothing Dominik Wagner Basim Khajwal C.-H. Luke Ong 19 0 0 19 Feb 2024
Monte Carlo with kernel-based Gibbs measures: Guarantees for probabilistic herding Martin Rouault Rémi Bardenet Mylène Maïda 41 0 0 18 Feb 2024
Dynamic planning in hierarchical active inference Matteo Priorelli Ivilin Peev Stoianov AI4CE 30 4 0 18 Feb 2024
Uncertainty Quantification of Graph Convolution Neural Network Models of Evolving Processes J. Hauth C. Safta Xun Huan Ravi G. Patel Reese E. Jones BDL UQCV 31 2 0 17 Feb 2024
Predictive Uncertainty Quantification via Risk Decompositions for Strictly Proper Scoring Rules Nikita Kotelevskii Maxim Panov PER UQCV UD 34 3 0 16 Feb 2024
Recommendations for Baselines and Benchmarking Approximate Gaussian Processes Sebastian W. Ober A. Artemev Marcel Wagenlander Rudolfs Grobins Mark van der Wilk GP 18 1 0 15 Feb 2024
Diffeomorphic Measure Matching with Kernels for Generative Modeling Biraj Pandey Bamdad Hosseini Pau Batlle H. Owhadi 23 3 0 12 Feb 2024
Improvement and generalization of ABCD method with Bayesian inference Ezequiel Alvarez L. Rold Manuel Szewc A. Szynkman Santiago A. Tanco Tatiana Tarutina 14 3 0 12 Feb 2024
Generative Modeling of Discrete Joint Distributions by E-Geodesic Flow Matching on Assignment Manifolds Bastian Boll Daniel Gonzalez-Alvarado Christoph Schnörr DRL 45 4 0 12 Feb 2024
The Relevance Feature and Vector Machine for health applications Albert Belenguer-Llorens C. Sevilla-Salcedo Emilio Parrado-Hernández Vanessa Gómez-Verdejo 9 0 0 11 Feb 2024
SAE: Single Architecture Ensemble Neural Networks Martin Ferianc Hongxiang Fan Miguel R. D. Rodrigues UQCV 15 0 0 09 Feb 2024
Domain Generalization with Small Data Kecheng Chen Elena Gal Hong Yan Haoliang Li OOD 27 5 0 09 Feb 2024
Wasserstein Gradient Flows for Moreau Envelopes of f-Divergences in Reproducing Kernel Hilbert Spaces Viktor Stein Sebastian Neumayer Gabriele Steidl Nicolaj Rux 50 9 0 07 Feb 2024
Variational Shapley Network: A Probabilistic Approach to Self-Explaining Shapley values with Uncertainty Quantification Mert Ketenci Inigo Urteaga Victor Alfonso Rodriguez Noémie Elhadad A. Perotte FAtt 22 0 0 06 Feb 2024
Bayesian Uncertainty for Gradient Aggregation in Multi-Task Learning Idan Achituve I. Diamant Arnon Netzer Gal Chechik Ethan Fetaya UQCV 32 4 0 06 Feb 2024