Variational Inference

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Latest papers 139

14 papers in the last four weeks, against 1 the four weeks before. 0.1% of all new papers.

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Variational Neural Belief Parameterizations for Robust Dexterous Grasping under Multimodal Uncertainty
Apr 28, 2026Clinton Enwerem, Shreya Kalyanaraman, John S. Baras +1Belief-Space Planning Stochastic Optimization
Department of Electrical & Computer Engineering and Institute for Systems Research, University of Maryland, College Park, MD, USA
Occam's Razor is Only as Sharp as Your ELBO
Apr 28, 2026Ethan Harvey, Geoff Pleiss, Michael C. HughesModel Selection Bayesian Inference
Tufts University
Heterogeneous Variational Inference for Markov Degradation Hazard Models: Discretized Mixture with Interpretable Clusters
Apr 27, 2026Takato YasunoLatent Variable Models Markov Models
Digital Business Department, Yachiyo Engineering Co., Ltd.
Reparameterization through Coverings and Topological Weight Priors
Apr 26, 2026Maxim Beketov, Pavel SnopovVariational Autoencoders Variational Inference
Even More Guarantees for Variational Inference in the Presence of Symmetries
Apr 23, 2026Lena Zellinger, Antonio VergariVariational Inference
School of Informatics University of Edinburgh
Symmetry Guarantees Statistic Recovery in Variational Inference
Apr 20, 2026Daniel Marks, Dario Paccagnan, Mark van der WilkVariational Inference
Department of Computer Science University of Oxford · Department of Computing Imperial College London
How to Approximate Inference with Subtractive Mixture Models
Apr 17, 2026Lena Zellinger, Nicola Branchini, Lennert De Smet +3Importance Sampling Variational Inference
University of Edinburgh · University of Warwick · KU Leuven
A Synonymous Variational Perspective on the Rate-Distortion-Perception Tradeoff
Apr 16, 2026Zijian Liang, Kai Niu, Changshuo Wang +2Rate-Distortion Theory Rate-Distortion Optimization
Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876, China · State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
Monte Carlo Stochastic Depth for Uncertainty Estimation in Deep Learning
Apr 14, 2026Adam T. Müller, Tobias Rögelein, Nicolaj C. StacheUncertainty Quantification Uncertainty Calibration
Heilbronn University of Applied Sciences, Germany
Differentiable free energy surface: a variational approach to directly observing rare events using generative deep-learning models
Apr 10, 2026Shuo-Hui Li, Chen Chen, Yao-Wen Zhang +1Free Energy Calculation Rare-Event Estimation
Department of Physics, The Hong Kong University of Science and Technology, Hong Kong, China · Department of Chemistry, The Hong Kong University of Science and Technology, Hong Kong, China · IAS Center for AI for Scientific Discoveries, Hong Kong University of Science and Technology, Hong Kong, China
Practical Bayesian Inference for Speech SNNs: Uncertainty and Loss-Landscape Smoothing
Apr 9, 2026Yesmine Abdennadher, Philip N. GarnerSpiking Neural Networks Bayesian Neural Networks
Idiap Research Institute, Martigny, Switzerland
Variational Approximated Restricted Maximum Likelihood Estimation for Spatial Data
Apr 8, 2026Debjoy ThakurVariational Inference
Washington University in St. Louis, USA · Ahmedabad University, India
Instance-Adaptive Parametrization for Amortized Variational Inference
Apr 8, 2026Andrea Pollastro, Andrea Apicella, Francesco Isgrò +1Variational Autoencoders Amortized Inference
Department of Electrical Engineering and Information Technology, University of Naples Federico II, 80125, Naples, Italy · Department of Information Engineering, Electrical Engineering, and Applied Mathematics, University of Salerno, 84084, Fisciano (Salerno), Italy
Avoiding Non-Integrable Beliefs in Expectation Propagation
Apr 5, 2026Zilu Zhao, Jichao Chen, Dirk SlockBayesian Inference Variational Inference
Communication Systems Department, EURECOM, France
State estimations and noise identifications with intermittent corrupted observations via Bayesian variational inference
Apr 3, 2026Peng Sun, Ruoyu Wang, Xue LuoRobust Estimation Covariance Estimation
School of Mathematical Sciences, Beihang University, Beijing, P. R. China 102206. · School of Mathematical Sciences, Beihang University, Beijing, P. R. China 102206, and Key Laboratory of Mathematics, Informatics and Behavioral Semantics (LMIB), Beihang University, Beijing, P. R. China 100191.
Inverse-Free Sparse Variational Gaussian Processes
Apr 1, 2026Stefano Cortinovis, Laurence Aitchison, Stefanos Eleftheriadis +1Gaussian Processes Variational Inference
University of Oxford · University of Bristol
Variational Graph Neural Networks for Uncertainty Quantification in Inverse Problems
Mar 31, 2026David Gonzalez, Alba Muixi, Beatriz Moya +1Uncertainty Quantification Graph Neural Networks
Keysight-UZ Chair of the Spanish National Strategy on AI. Aragon Institute of Engineering Research (I3A), Universidad de Zaragoza, Spain · Laboratori de Càlcul Numèric (LaCàn), Universitat Politècnica de Catalunya - BarcelonaTech (UPC), Spain · Centre Internacional de Mètodes Numèrics en Enginyeria (CIMNE), Barcelona, Spain +1
Variational Learning of Fractional Posteriors
Mar 29, 2026Kian Ming A. Chai, Edwin V. BonillaBayesian Inference Variational Inference
DSO National Laboratories, Singapore · CSIRO’s Data61, Australia
Stepwise Variational Inference with Vine Copulas
Mar 24, 2026Elisabeth Griesbauer, Leiv Rønneberg, Arnoldo Frigessi +2Variational Inference Copula Models
Norwegian Computing Center, Oslo, Norway · Oslo Centre for Biostatistics and Epidemiology (OCBE), University of Oslo, Norway · Integreat - Norwegian Centre for Knowledge-driven Machine Learning, Oslo, Norway +3
Amortized Variational Inference for Logistic Regression with Missing Covariates
Mar 22, 2026M. Cherifi, Aude Sportisse, Xujia Zhu +2Learning with Missing Data Logistic Regression
Lab. Traitement du signal, Ecole Militaire Polytechnique, BP 17 Bordj El Bahri, Algeria · Lab. d’Informatique de Grenoble, CNRS, France · University of Paris Saclay, CNRS, CentraleSupelec, Laboratoire des signaux et systèmes, 91190, Gif-sur-Yvette, France
Stability of Sequential and Parallel Coordinate Ascent Variational Inference
Mar 21, 2026Debdeep PatiVariational Inference
Department of Statistics, University of Wisconsin-Madison, Madison, WI 53706
Var-JEPA: A Variational Formulation of the Joint-Embedding Predictive Architecture - Bridging Predictive and Generative Self-Supervised Learning
Mar 20, 2026Moritz Gögl, Christopher YauJoint-Embedding Predictive Architecture Self-Supervised Learning
University of Oxford, UK · Health Data Research UK
Variational Rectification Inference for Learning with Noisy Labels
Mar 18, 2026Haoliang Sun, Qi Wei, Lei Feng +4Learning with Noisy Labels Variational Inference
School of Software, Shandong University, Jinan, China. · School of Computer Science and Engineering, Nanyang Technological University, Singapore. · School of Computing, National University of Singapore, Singapore. +1
Adaptive regularization parameter selection for high-dimensional inverse problems: A Bayesian approach with Tucker low-rank constraints
Mar 17, 2026Qing-Mei Yang, Da-Qing ZhangBayesian Inverse Problems Image Inverse Problems
School of Science, University of Science and Technology Liaoning, Anshan, Liaoning Province, 114051, PR China
Exploring the Dimensions of a Variational Neuron
Mar 14, 2026Yves RuffenachLatent Variable Models Variational Inference
Conservatoire National des Arts et Métiers
Variational Garrote for Sparse Inverse Problems
Mar 13, 2026Kanghun Lee, Hyungjoon Soh, Junghyo JoSparse Recovery Variational Inference
Department of Science Education, Seoul National University, Seoul, 08826, Korea · Center for Theoretical Physics and Artificial Intelligence Institute, Seoul National University, Seoul, 08826, Korea · School of Computational Sciences, Korea Institute for Advanced Study, Seoul, 02455, Korea
Slack More, Predict Better: Proximal Relaxation for Probabilistic Latent Variable Model-based Soft Sensors
Mar 12, 2026Zehua Zou, Yiran Ma, Yulong Zhang +5Latent Variable Models Variational Inference
the Hangzhou International Innovation Institute, Beihang University, Hangzhou 311115, China · the State Key Laboratory of Industrial Control Technology, College of Control science and Engineering, Zhejiang University, Hangzhou 310027, Zhejiang, China · the College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108, China +4
Variational Routing: A Scalable Bayesian Framework for Calibrated Mixture-of-Experts Transformers
Mar 10, 2026Albus Yizhuo Li, Matthew WickerUncertainty Quantification Mixture-of-Experts Models
Department of Computing, Imperial College London.
Active Flow Matching
Mar 1, 2026Yashvir S. Grewal, Daniel M. Steinberg, Thang D. Bui +2Flow-Based Generative Modeling Black-Box Optimization
School of Computing, College of Systems and Society, Australian National University, Australia · Data61, CSIRO, Australia
Neural Diffusion Intensity Models for Point Process Data
Feb 27, 2026Xinlong Du, Harsha Honnappa, Vinayak RaoTemporal Point Processes Variational Inference
Edwardson School of Industrial Engineering, Purdue University · Department of Statistics, Purdue University

Apr 28, 2026J/K move · Enter open · S save

Variational Neural Belief Parameterizations for Robust Dexterous Grasping under Multimodal Uncertainty

Clinton Enwerem, Shreya Kalyanaraman, John S. Baras, Calin Belta

Department of Electrical & Computer Engineering and Institute for Systems Research, University of Maryland, College Park, MD, USA

Belief-Space Planning Stochastic Optimization Robotic Grasping Variational Inference Decision-Making under Uncertainty

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Contact variability, sensing uncertainty, and external disturbances make grasp execution stochastic. Expected-quality objectives ignore tail outcomes and often select grasps that fail under adverse contact realizations. Risk-sensitive POMDPs address this failure mode, but many use particle-filter beliefs that scale poorly, obstruct gradient-based optimization, and estimate Conditional Value-at-Risk (CVaR) with high-variance approximations. We instead formulate grasp acquisition as variational inference over latent contact parameters and object pose, representing the belief with a differentiable Gaussian mixture. We use Gumbel-Softmax component selection and location-scale reparameterization to express samples as smooth functions of the belief parameters, enabling pathwise gradients through a differentiable CVaR surrogate for direct optimization of tail robustness. In simulation, our variational neural belief improves robust grasp success under contact-parameter uncertainty and exogenous force perturbations while reducing planning time by roughly an order of magnitude relative to particle-filter model-predictive control. On a serial-chain robot arm with a multifingered hand, we validate grasp-and-lift success under object-pose uncertainty against a Gaussian baseline. Both methods succeed on the tested perturbations, but our controller terminates in fewer steps and less wall-clock time while achieving a higher tactile grasp-quality proxy. Our learned belief also calibrates risk more accurately, keeping mean absolute calibration error below 0.14 across tested simulation regimes, compared with 0.58 for a Cross-Entropy Method planner.