Variational Inference: A Review for Statisticians

4 January 2016

Papers citing "Variational Inference: A Review for Statisticians"

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Title
Identifying Causal Direction via Variational Bayesian Compression Quang-Duy Tran Bao Duong Phuoc Nguyen Thin Nguyen CML 34 0 0 12 May 2025
Combining Bayesian Inference and Reinforcement Learning for Agent Decision Making: A Review Chengmin Zhou Ville Kyrki P. Fränti Laura Ruotsalainen BDL AI4CE 42 0 0 12 May 2025
Taming OOD Actions for Offline Reinforcement Learning: An Advantage-Based Approach Xuyang Chen Keyu Yan Lin Zhao OffRL 51 0 0 08 May 2025
Boosting Statistic Learning with Synthetic Data from Pretrained Large Models Jialong Jiang Wenkang Hu Jian Huang Yuling Jiao Xu Liu DiffM 50 0 0 08 May 2025
Variational Formulation of the Particle Flow Particle Filter Yinzhuang Yi Jorge Cortés Nikolay A. Atanasov 36 0 0 06 May 2025
Latent Adaptive Planner for Dynamic Manipulation Donghun Noh Deqian Kong Minglu Zhao Andrew Lizarraga Jianwen Xie Ying Nian Wu Dennis W. Hong 115 0 0 06 May 2025
Bayesian Robust Aggregation for Federated Learning Aleksandr Karakulev Usama Zafar Salman Toor Prashant Singh FedML 33 0 0 05 May 2025
Bayesian Optimization-based Tire Parameter and Uncertainty Estimation for Real-World Data Sven Goblirsch Benedikt Ruhland Johannes Betz Markus Lienkamp 32 0 0 29 Apr 2025
Evolution of Gaussians in the Hellinger-Kantorovich-Boltzmann gradient flow Matthias Liero Alexander Mielke Oliver Tse Jia Jie Zhu 29 0 0 29 Apr 2025
Factor Analysis with Correlated Topic Model for Multi-Modal Data Małgorzata Łazęcka Ewa Szczurek 23 0 0 26 Apr 2025
Uncertainty quantification of neural network models of evolving processes via Langevin sampling C. Safta Reese E. Jones Ravi G. Patel Raelynn Wonnacot Dan S. Bolintineanu Craig M. Hamel S. Kramer BDL 36 0 0 21 Apr 2025
Segmentation with Noisy Labels via Spatially Correlated Distributions Ryu Tadokoro Tsukasa Takagi Shin-ichi Maeda 24 0 0 21 Apr 2025
Variational Autoencoder Framework for Hyperspectral Retrievals (Hyper-VAE) of Phytoplankton Absorption and Chlorophyll a in Coastal Waters for NASA's EMIT and PACE Missions Jiadong Lou Bingqing Liu Yuanheng Xiong Xiaodong Zhang Xu Yuan 21 0 0 18 Apr 2025
An Image is Worth $K$ Topics: A Visual Structural Topic Model with Pretrained Image Embeddings Matías Piqueras Alexandra Segerberg Matteo Magnani Måns Magnusson Nataša Sladoje 37 0 0 14 Apr 2025
Ensemble-Enhanced Graph Autoencoder with GAT and Transformer-Based Encoders for Robust Fault Diagnosis Moirangthem Tiken Singh AI4CE 34 1 0 13 Apr 2025
Stacking Variational Bayesian Monte Carlo Francesco Silvestrin Chengkun Li Luigi Acerbi BDL 42 0 0 07 Apr 2025
PRISM: Probabilistic Representation for Integrated Shape Modeling and Generation Lei Cheng Mahdi Saleh Qing Cheng Lu Sang Hongli Xu Daniel Cremers F. Tombari 23 0 0 06 Apr 2025
Variational Self-Supervised Learning Mehmet Can Yavuz Berrin Yanikoglu SSL 102 0 0 06 Apr 2025
Stochastic Variational Inference with Tuneable Stochastic Annealing John Paisley G. Fazelnia Brian Barr 24 0 0 04 Apr 2025
Taming High-Dimensional Dynamics: Learning Optimal Projections onto Spectral Submanifolds Hugo Buurmeijer Luis A. Pabon J. I. Alora Roshan S. Kaundinya George Haller Marco Pavone 31 0 0 04 Apr 2025
Multi-fidelity Parameter Estimation Using Conditional Diffusion Models Caroline Tatsuoka Minglei Yang Dongbin Xiu Guannan Zhang DiffM 41 1 0 02 Apr 2025
Probabilistic Curriculum Learning for Goal-Based Reinforcement Learning Llewyn Salt Marcus Gallagher 31 1 0 02 Apr 2025
Sparse Gaussian Neural Processes Tommy Rochussen Vincent Fortuin BDL UQCV 56 0 0 02 Apr 2025
Locally Orderless Images for Optimization in Differentiable Rendering Ishit Mehta Manmohan Chandraker Ravi Ramamoorthi 29 0 0 27 Mar 2025
Learning to chain-of-thought with Jensen's evidence lower bound Yunhao Tang Sid Wang Rémi Munos BDL OffRL LRM 50 0 0 25 Mar 2025
FisherTune: Fisher-Guided Robust Tuning of Vision Foundation Models for Domain Generalized Segmentation Dong Zhao Jinlong Li Shuang Wang Mengyao Wu Qi Zang N. Sebe Zhun Zhong 141 0 0 23 Mar 2025
Evaluating Negative Sampling Approaches for Neural Topic Models Suman Adhya Avishek Lahiri Debarshi Kumar Sanyal Partha Pratim Das BDL 45 0 0 23 Mar 2025
Quantification of Uncertainties in Probabilistic Deep Neural Network by Implementing Boosting of Variational Inference Pavia Bera Sanjukta Bhanja UQCV BDL 80 0 0 18 Mar 2025
Uncertainty Quantification for Data-Driven Machine Learning Models in Nuclear Engineering Applications: Where We Are and What Do We Need? Xu Wu L. Moloko P. Bokov Gregory K. Delipei Joshua Kaizer K. Ivanov AI4CE 44 0 0 16 Mar 2025
Massively Parallel Expectation Maximization For Approximate Posteriors Thomas Heap Sam Bowyer Laurence Aitchison 44 0 0 11 Mar 2025
Vairiational Stochastic Games Zhiyu Zhao Haifeng Zhang 55 0 0 08 Mar 2025
Mixed Likelihood Variational Gaussian Processes Kaiwen Wu Craig Sanders Benjamin Letham Phillip Guan 77 0 0 06 Mar 2025
Parameter Expanded Stochastic Gradient Markov Chain Monte Carlo Hyunsu Kim G. Nam Chulhee Yun Hongseok Yang Juho Lee BDL UQCV 57 0 0 02 Mar 2025
End-To-End Learning of Gaussian Mixture Priors for Diffusion Sampler Denis Blessing Xiaogang Jia Gerhard Neumann DiffM 45 0 0 01 Mar 2025
Bayesian Active Learning for Multi-Criteria Comparative Judgement in Educational Assessment Andy Gray Alma A. M. Rahat Tom Crick Stephen Lindsay ELM 37 1 0 01 Mar 2025
Variational Bayesian Pseudo-Coreset Hyungi Lee S. Lee Juho Lee BDL 36 0 0 28 Feb 2025
Training Robust Graph Neural Networks by Modeling Noise Dependencies Yeonjun In Kanghoon Yoon Sukwon Yun Kibum Kim Sungchul Kim Chanyoung Park OOD NoLa 76 0 0 27 Feb 2025
Transfer Learning in Latent Contextual Bandits with Covariate Shift Through Causal Transportability Mingwei Deng Ville Kyrki Dominik Baumann 41 0 0 27 Feb 2025
Actively Inferring Optimal Measurement Sequences Catherine F. Higham Paul Henderson R. Murray-Smith DRL 59 0 0 25 Feb 2025
Federated Variational Inference for Bayesian Mixture Models Jackie Rao Francesca L. Crowe Tom Marshall S. Richardson Paul D. W. Kirk FedML 95 0 0 18 Feb 2025
In-Context Parametric Inference: Point or Distribution Estimators? Sarthak Mittal Yoshua Bengio Nikolay Malkin Guillaume Lajoie 72 0 0 17 Feb 2025
Properties of Wasserstein Gradient Flows for the Sliced-Wasserstein Distance Christophe Vauthier Quentin Mérigot Anna Korba 37 0 0 10 Feb 2025
Amortized In-Context Bayesian Posterior Estimation Sarthak Mittal Niels Leif Bracher Guillaume Lajoie P. Jaini Marcus A. Brubaker 62 1 0 10 Feb 2025
A Revisit of Total Correlation in Disentangled Variational Auto-Encoder with Partial Disentanglement Chengrui Li Yunmiao Wang Yule Wang Weihan Li Dieter Jaeger Anqi Wu CoGe DRL 74 0 0 04 Feb 2025
Distribution Transformers: Fast Approximate Bayesian Inference With On-The-Fly Prior Adaptation George Whittle Juliusz Ziomek Jacob Rawling Michael A. Osborne 87 2 0 04 Feb 2025
Learning Hyperparameters via a Data-Emphasized Variational Objective Ethan Harvey Mikhail Petrov Michael C. Hughes 63 0 0 03 Feb 2025
Scalable Language Models with Posterior Inference of Latent Thought Vectors Deqian Kong Minglu Zhao Dehong Xu Bo Pang Shu Wang ... Zhangzhang Si Chuan Li Jianwen Xie Sirui Xie Ying Nian Wu VLM LRM BDL 81 5 0 03 Feb 2025
HuViDPO:Enhancing Video Generation through Direct Preference Optimization for Human-Centric Alignment Lifan Jiang Boxi Wu Jiahui Zhang Xiaotong Guan Shuang Chen VGen 61 1 0 02 Feb 2025
Hellinger-Kantorovich Gradient Flows: Global Exponential Decay of Entropy Functionals Alexander Mielke Jia Jie Zhu 58 1 0 28 Jan 2025
Robust and highly scalable estimation of directional couplings from time-shifted signals Luca Ambrogioni Louis Rouillard Demian Wassermann 54 0 0 28 Jan 2025