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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
Learning Optimal Filters Using Variational Inference Enoch Luk Eviatar Bach Ricardo Baptista Andrew Stuart 88 7 0 26 Jun 2024
Efficient, Multimodal, and Derivative-Free Bayesian Inference With Fisher-Rao Gradient Flows Yifan Chen Daniel Zhengyu Huang Jiaoyang Huang Sebastian Reich Andrew M. Stuart 74 7 0 25 Jun 2024
Tree-based variational inference for Poisson log-normal models Alexandre Chaussard Anna Bonnet Elisabeth Gassiat Sylvain Le Corff 65 0 0 25 Jun 2024
Peirce in the Machine: How Mixture of Experts Models Perform Hypothesis Construction Bruce Rushing MoE 50 0 0 24 Jun 2024
VICatMix: variational Bayesian clustering and variable selection for discrete biomedical data Paul D. W. Kirk Jackie Rao 132 1 0 23 Jun 2024
Hardware-Aware Neural Dropout Search for Reliable Uncertainty Prediction on FPGA Zehuan Zhang Hongxiang Fan Hao Mark Chen Lukasz Dudziak Wayne Luk BDL 70 0 0 23 Jun 2024
Recursive variational Gaussian approximation with the Whittle likelihood for linear non-Gaussian state space models Bao Anh Vu David Gunawan Andrew Zammit-Mangion 73 1 0 23 Jun 2024
Probabilistic Programming with Programmable Variational Inference McCoy R. Becker Alexander K. Lew Xiaoyan Wang Matin Ghavami Mathieu Huot Martin Rinard Vikash K. Mansinghka 131 5 0 22 Jun 2024
Flexible Tails for Normalizing Flows Tennessee Hickling Dennis Prangle 64 0 0 22 Jun 2024
On Naive Mean-Field Approximation for high-dimensional canonical GLMs Soumendu Sundar Mukherjee Jiaze Qiu Subhabrata Sen 63 1 0 21 Jun 2024
Hierarchical thematic classification of major conference proceedings Arsentii Kuzmin Alexander Aduenko Vadim Strijov 36 0 0 21 Jun 2024
Bayesian Bandit Algorithms with Approximate Inference in Stochastic Linear Bandits Ziyi Huang Henry Lam Haofeng Zhang 87 0 0 20 Jun 2024
A variational Bayes approach to debiased inference for low-dimensional parameters in high-dimensional linear regression Ismaël Castillo Alice L'Huillier Kolyan Ray Luke Travis 67 0 0 18 Jun 2024
Variational Distillation of Diffusion Policies into Mixture of Experts Hongyi Zhou Denis Blessing Ge Li Onur Celik Xiaogang Jia Gerhard Neumann Rudolf Lioutikov DiffM 74 4 0 18 Jun 2024
Online Pareto-Optimal Decision-Making for Complex Tasks using Active Inference Peter Amorese Shohei Wakayama Nisar R. Ahmed Morteza Lahijanian 72 3 0 17 Jun 2024
Symmetry-driven embedding of networks in hyperbolic space Simon Lizotte Jean-Gabriel Young Antoine Allard 83 1 0 15 Jun 2024
Active Inference Meeting Energy-Efficient Control of Parallel and Identical Machines Yavar Taheri Yeganeh Mohsen Jafari Andrea Matta 86 1 0 13 Jun 2024
Adaptive Slot Attention: Object Discovery with Dynamic Slot Number Ke Fan Zechen Bai Tianjun Xiao Tong He Max Horn Yanwei Fu Francesco Locatello Zheng Zhang OCL 97 10 0 13 Jun 2024
A geometric approach to informed MCMC sampling Vivekananda Roy 78 0 0 13 Jun 2024
Global Tests for Smoothed Functions in Mean Field Variational Additive Models Mark J. Meyer Junyi Wei 35 0 0 12 Jun 2024
Balancing Molecular Information and Empirical Data in the Prediction of Physico-Chemical Properties Johannes Zenn Dominik Gond Fabian Jirasek Robert Bamler 49 2 0 12 Jun 2024
Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling Denis Blessing Xiaogang Jia Johannes Esslinger Francisco Vargas Gerhard Neumann 146 27 0 11 Jun 2024
Convergence rate of random scan Coordinate Ascent Variational Inference under log-concavity Hugo Lavenant Giacomo Zanella 63 5 0 11 Jun 2024
A Concise Mathematical Description of Active Inference in Discrete Time Jesse van Oostrum Carlotta Langer Nihat Ay 78 1 0 11 Jun 2024
Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians Tom Huix Anna Korba Alain Durmus Eric Moulines 89 9 0 06 Jun 2024
Approximation-Aware Bayesian Optimization Natalie Maus Kyurae Kim Geoff Pleiss David Eriksson John P. Cunningham Jacob R. Gardner 69 3 0 06 Jun 2024
You Only Accept Samples Once: Fast, Self-Correcting Stochastic Variational Inference Dominic B. Dayta TPM BDL 55 0 0 05 Jun 2024
Posterior and variational inference for deep neural networks with heavy-tailed weights Ismael Castillo Paul Egels BDL 126 4 0 05 Jun 2024
Ai-Sampler: Adversarial Learning of Markov kernels with involutive maps Evgenii Egorov Ricardo Valperga E. Gavves BDL GAN 81 1 0 04 Jun 2024
Disentangled Representation via Variational AutoEncoder for Continuous Treatment Effect Estimation Ruijing Cui Jianbin Sun Bingyu He Kewei Yang Bingfeng Ge 69 0 0 04 Jun 2024
Understanding Stochastic Natural Gradient Variational Inference Kaiwen Wu Jacob R. Gardner BDL 89 2 0 04 Jun 2024
Diffusion Boosted Trees Xizewen Han Mingyuan Zhou AI4CE 111 0 0 03 Jun 2024
Logistic Variational Bayes Revisited M. Komodromos Marina Evangelou Sarah Filippi BDL 57 0 0 02 Jun 2024
Representation and De-interleaving of Mixtures of Hidden Markov Processes Jiadi Bao Mengtao Zhu Yunjie Li Shafei Wang 31 0 0 01 Jun 2024
Flexible inference in heterogeneous and attributed multilayer networks Martina Contisciani Marius Hobbhahn Eleanor A. Power Philipp Hennig Caterina De Bacco 91 2 0 31 May 2024
Enhancing Generative Molecular Design via Uncertainty-guided Fine-tuning of Variational Autoencoders Naﬁz Abeer Sanket Jantre Nathan M. Urban Byung-Jun Yoon 87 0 0 31 May 2024
Scalable Bayesian Learning with posteriors Samuel Duffield Kaelan Donatella Johnathan Chiu Phoebe Klett Daniel Simpson BDL UQCV 182 2 0 31 May 2024
Recurrent Deep Kernel Learning of Dynamical Systems N. Botteghi Paolo Motta Andrea Manzoni P. Zunino Mengwu Guo 60 1 0 30 May 2024
Understanding and mitigating difficulties in posterior predictive evaluation Abhinav Agrawal Justin Domke UQCV 74 0 0 30 May 2024
Physics-Aware Neural Implicit Solvers for multiscale, parametric PDEs with applications in heterogeneous media Matthaios Chatzopoulos P. Koutsourelakis AI4CE 81 3 0 29 May 2024
Kernel Semi-Implicit Variational Inference Ziheng Cheng Longlin Yu Tianyu Xie Shiyue Zhang Cheng Zhang 57 7 0 29 May 2024
Preferred-Action-Optimized Diffusion Policies for Offline Reinforcement Learning Tianle Zhang Jiayi Guan Lin Zhao Yihang Li Dongjiang Li ... Lei Sun Yue Chen Xuelong Wei Lusong Li Xiaodong He 92 2 0 29 May 2024
Evaluating Bayesian deep learning for radio galaxy classification Devina Mohan Anna M. M. Scaife UQCV BDL 131 1 0 28 May 2024
FASTopic: A Fast, Adaptive, Stable, and Transferable Topic Modeling Paradigm Xiaobao Wu Thong Nguyen Delvin Ce Zhang William Yang Wang Anh Tuan Luu 124 17 0 28 May 2024
Modeling Dynamic Topics in Chain-Free Fashion by Evolution-Tracking Contrastive Learning and Unassociated Word Exclusion Xiaobao Wu Xinshuai Dong Liangming Pan Thong Nguyen Anh Tuan Luu 134 14 0 28 May 2024
SEMF: Supervised Expectation-Maximization Framework for Predicting Intervals Ilia Azizi M. Boldi V. Chavez-Demoulin 148 0 0 28 May 2024
Bayesian RG Flow in Neural Network Field Theories Jessica N. Howard Marc S. Klinger Anindita Maiti A. G. Stapleton 135 2 0 27 May 2024
Diffusion-Reward Adversarial Imitation Learning Chun-Mao Lai Hsiang-Chun Wang Ping-Chun Hsieh Yu-Chiang Frank Wang Min-Hung Chen Shao-Hua Sun 83 9 0 25 May 2024
Federated Learning for Non-factorizable Models using Deep Generative Prior Approximations Conor Hassan Joshua J Bon Elizaveta Semenova Antonietta Mira Kerrie Mengersen 53 0 0 25 May 2024
Differentiable Annealed Importance Sampling Minimizes The Jensen-Shannon Divergence Between Initial and Target Distribution Johannes Zenn Robert Bamler 61 1 0 23 May 2024