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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
Amortized Variational Inference for Deep Gaussian Processes Qiuxian Meng Yongyou Zhang 35 0 0 18 Sep 2024
HJ-sampler: A Bayesian sampler for inverse problems of a stochastic process by leveraging Hamilton-Jacobi PDEs and score-based generative models Tingwei Meng Zongren Zou Jérome Darbon George Karniadakis DiffM 86 2 0 15 Sep 2024
Improved Finite-Particle Convergence Rates for Stein Variational Gradient Descent Sayan Banerjee Krishnakumar Balasubramanian Promit Ghosal 90 4 0 13 Sep 2024
Review of Recent Advances in Gaussian Process Regression Methods Chenyi Lyu Xingchi Liu Lyudmila Mihaylova GP 62 3 0 12 Sep 2024
Portfolio Stress Testing and Value at Risk (VaR) Incorporating Current Market Conditions Krishan Mohan Nagpal 54 0 0 12 Sep 2024
A Primer on Variational Inference for Physics-Informed Deep Generative Modelling Alex Glyn-Davies Arnaud Vadeboncoeur O. Deniz Akyildiz Ieva Kazlauskaite Mark Girolami PINN 141 0 0 10 Sep 2024
Predicting Critical Heat Flux with Uncertainty Quantification and Domain Generalization Using Conditional Variational Autoencoders and Deep Neural Networks Farah Alsafadi Aidan Furlong Xu Wu UQCV AI4CE 105 3 0 09 Sep 2024
Towards Autonomous Cybersecurity: An Intelligent AutoML Framework for Autonomous Intrusion Detection Li Yang Abdallah Shami 75 2 0 05 Sep 2024
Gradient-free variational learning with conditional mixture networks Conor Heins Hao Wu Dimitrije Marković Alexander Tschantz Jeff Beck Christopher L. Buckley BDL 92 3 0 29 Aug 2024
Constrained Diffusion Models via Dual Training Shervin Khalafi Dongsheng Ding Alejandro Ribeiro 111 4 0 27 Aug 2024
Decentralised Variational Inference Frameworks for Multi-object Tracking on Sensor Network Qing Li Runze Gan S. Godsill 129 1 0 24 Aug 2024
Amortized Bayesian Multilevel Models Daniel Habermann Marvin Schmitt Lars Kühmichel Andreas Bulling Stefan T. Radev Paul-Christian Bürkner 252 4 0 23 Aug 2024
Variance reduction of diffusion model's gradients with Taylor approximation-based control variate Paul Jeha Will Grathwohl Michael Riis Andersen Carl Henrik Ek J. Frellsen DiffM 106 1 0 22 Aug 2024
Personalizing Reinforcement Learning from Human Feedback with Variational Preference Learning S. Poddar Yanming Wan Hamish Ivison Abhishek Gupta Natasha Jaques 104 50 0 19 Aug 2024
Modelling the Distribution of Human Motion for Sign Language Assessment Oliver Cory Ozge Mercanoglu Sincan M. Vowels A. Battisti F. Holzknecht Katja Tissi Sandra Sidler-Miserez Tobias Haug Sarah Ebling Richard Bowden 109 1 0 19 Aug 2024
Learning to Explore for Stochastic Gradient MCMC Seunghyun Kim Seohyeon Jung Seonghyeon Kim Juho Lee BDL 104 1 0 17 Aug 2024
Unsupervised Variational Translator for Bridging Image Restoration and High-Level Vision Tasks Jiawei Wu Zhi Jin 70 0 0 15 Aug 2024
Fast Bayesian inference in a class of sparse linear mixed effects models M. Spyropoulou J. Hopker J. E. Griffin 57 0 0 14 Aug 2024
Quantification of total uncertainty in the physics-informed reconstruction of CVSim-6 physiology Mario De Florio Zongren Zou Daniele E. Schiavazzi George Karniadakis 56 4 0 13 Aug 2024
Value of Information and Reward Specification in Active Inference and POMDPs Ran Wei 81 3 0 13 Aug 2024
Variational Bayesian Phylogenetic Inference with Semi-implicit Branch Length Distributions Tianyu Xie Frederick A. Matsen IV M. Suchard Cheng Zhang 54 1 0 09 Aug 2024
Re-ENACT: Reinforcement Learning for Emotional Speech Generation using Actor-Critic Strategy Ravi Shankar Archana Venkataraman 62 0 0 04 Aug 2024
Alpha-VI DeepONet: A prior-robust variational Bayesian approach for enhancing DeepONets with uncertainty quantification Soban Nasir Lone Subhayan De R. Nayek BDL 68 1 0 01 Aug 2024
Weak neural variational inference for solving Bayesian inverse problems without forward models: applications in elastography Vincent C. Scholz Yaohua Zang P. Koutsourelakis 91 3 0 30 Jul 2024
Causal effect estimation under network interference with mean-field methods Sohom Bhattacharya Subhabrata Sen CML 76 2 0 28 Jul 2024
Variational Inference Using Material Point Method Yongchao Huang 63 0 0 26 Jul 2024
Sparse Inducing Points in Deep Gaussian Processes: Enhancing Modeling with Denoising Diffusion Variational Inference Jian Xu Delu Zeng John Paisley DiffM 90 1 0 24 Jul 2024
Federated Automatic Latent Variable Selection in Multi-output Gaussian Processes Jingyi Gao Seokhyun Chung FedML 60 0 0 24 Jul 2024
Craft: Cross-modal Aligned Features Improve Robustness of Prompt Tuning Jingchen Sun Rohan Sharma Vishnu Suresh Lokhande Changyou Chen 105 0 0 22 Jul 2024
SoftCVI: Contrastive variational inference with self-generated soft labels Daniel Ward Mark Beaumont Matteo Fasiolo BDL 238 1 0 22 Jul 2024
Hyperspectral Unmixing Under Endmember Variability: A Variational Inference Framework Yuening Li Xiao Fu Junbin Liu Wing-Kin Ma 37 0 0 20 Jul 2024
Modeling Latent Neural Dynamics with Gaussian Process Switching Linear Dynamical Systems Amber Hu D. Zoltowski Aditya Nair David Anderson Lea Duncker Scott W. Linderman 135 3 0 19 Jul 2024
Semi-Supervised Generative Models for Disease Trajectories: A Case Study on Systemic Sclerosis Cécile Trottet Manuel Schürch Ahmed Allam Imon Barua L. Petelytska ... Mislav Radic Oliver Distler A. Hoffmann-Vold Michael Krauthammer Eustar collaborators MedIm 111 0 0 16 Jul 2024
Computationally Efficient Estimation of Large Probit Models Patrick Ding Guido Imbens Zhaonan Qu Yinyu Ye 80 0 0 12 Jul 2024
FedVAE: Trajectory privacy preserving based on Federated Variational AutoEncoder Yuchen Jiang Ying Wu Shiyao Zhang J. J. Yu 52 3 0 12 Jul 2024
Autoregressive Speech Synthesis without Vector Quantization Lingwei Meng Long Zhou Shujie Liu Sanyuan Chen Bing Han ... Jinyu Li Sheng Zhao Xixin Wu Helen M. Meng Furu Wei 161 43 0 11 Jul 2024
Deep Inverse Design for High-Level Synthesis Ping Chang Tosiron Adegbija Yuchao Liao Claudio Talarico Ao Li Janet Roveda 106 0 0 11 Jul 2024
Accelerating MRI Uncertainty Estimation with Mask-based Bayesian Neural Network Zehuan Zhang Matej Genci Hongxiang Fan A. Wetscherek Wayne Luk 73 0 0 07 Jul 2024
Sequential Gaussian Variational Inference for Nonlinear State Estimation applied to Robotic Applications Min-Won Seo Solmaz S. Kia 77 1 0 07 Jul 2024
posteriordb: Testing, Benchmarking and Developing Bayesian Inference Algorithms Måns Magnusson Jakob Torgander Paul-Christian Bürkner Lu Zhang Bob Carpenter Aki Vehtari 117 6 0 06 Jul 2024
Randomized Physics-Informed Neural Networks for Bayesian Data Assimilation Yifei Zong D. Barajas-Solano A. Tartakovsky 87 1 0 05 Jul 2024
Online Bayesian changepoint detection for network Poisson processes with community structure Joshua Corneck Edward A. K. Cohen James S. Martin Francesco Sanna Passino 3DPC 37 2 0 04 Jul 2024
Scalable expectation propagation for generalized linear models Niccolò Anceschi A. Fasano Beatrice Franzolini Giovanni Rebaudo 89 0 0 02 Jul 2024
Enabling Mixed Effects Neural Networks for Diverse, Clustered Data Using Monte Carlo Methods Andrej Tschalzev Paul Nitschke Lukas Kirchdorfer Stefan Lüdtke Christian Bartelt Heiner Stuckenschmidt 86 0 0 01 Jul 2024
An Expectation-Maximization Algorithm for Training Clean Diffusion Models from Corrupted Observations Weimin Bai Yifei Wang Wenzheng Chen He Sun 118 12 0 01 Jul 2024
Improving the performance of Stein variational inference through extreme sparsification of physically-constrained neural network models G. A. Padmanabha J. Fuhg Cosmin Safta Reese E. Jones N. Bouklas 80 5 0 30 Jun 2024
Particle Semi-Implicit Variational Inference Jen Ning Lim A. M. Johansen 118 7 0 30 Jun 2024
Electrostatics-based particle sampling and approximate inference Yongchao Huang DiffM 89 2 0 28 Jun 2024
Provably Efficient Posterior Sampling for Sparse Linear Regression via Measure Decomposition Andrea Montanari Yuchen Wu 83 4 0 27 Jun 2024
Torchtree: flexible phylogenetic model development and inference using PyTorch Mathieu Fourment Matthew Macaulay Christiaan J. Swanepoel Xiang Ji M. Suchard Frederick A Matsen IV BDL 109 0 0 26 Jun 2024