Gaussian Processes

Ask about this topic

Overview

Gaussian processes model unknown functions by using kernels to describe how values at different inputs relate, producing both predictions and uncertainty estimates. Research develops kernels for nonstationary, multi-output, deep, and structured data, alongside scalable inference methods such as inducing points, Vecchia approximations, Kronecker algebra, and matrix-free computation. These methods support applications including Bayesian optimization, spatial and time-series forecasting, robotics, scientific simulation, and uncertainty-aware classification. A central tension is how to scale inference and adapt kernels to complex data while retaining accurate, well-calibrated uncertainty and reliable decisions.

Latest papers

CardsList

115 papers24 papers in the last four weeks, up 71% on the four weeks before. 0.1% of all new papers.

  1. Inverse-Free Sparse Variational Gaussian Processes

    Apr 1, 2026Stefano Cortinovis, Laurence Aitchison, Stefanos Eleftheriadis +1Sparse Gaussian ProcessesGaussian Processes

    University of Oxford · University of Bristol

  2. Digital Twin-Assisted Measurement Design and Channel Statistics Prediction

    Mar 24, 2026Robin J. Williams, Mahmoud Saad Abouamer, Petar PopovskiRadio Propagation ModelingChannel Estimation

    Department of Electronic Systems, Aalborg University, Denmark

  3. Time-adaptive infinite-dimensional Gaussian process regression on manifolds

    Mar 22, 2026MD Ruiz-Medina, AE Madrid, A Torres-Signes +1Empirical BayesBayesian Inference

  4. On Additive Gaussian Processes for Wind Farm Power Prediction

    Mar 18, 2026Simon M. Brealy, Lawrence A. Bull, Daniel S. Brennan +4Wind Power ForecastingGaussian Processes

    Dynamics Research Group, Department of Mechanical Engineering, The University of Sheffield, Mappin Street, Sheffield, S1 3JD, UK · Computational Statistics and Machine Learning Group, Department of Engineering, University of Cambridge, Cambridge, CB3 0FA, UK · Vattenfall R&D, Vattenfall AB, Älvkarleby, Sweden

  5. Real-Time Online Learning for Model Predictive Control using a Spatio-Temporal Gaussian Process Approximation

    Mar 18, 2026Lars Bartels, Amon Lahr, Andrea Carron +1Model Predictive ControlGaussian Processes

    Institute for Dynamic Systems and Control, ETH Zürich, CH-8092 Zürich, Switzerland.

  6. Simplex-to-Euclidean Bijection for Conjugate and Calibrated Multiclass Gaussian Process Classification

    Mar 17, 2026Bernardo Williams, Harsha Vardhan Tetali, Arto Klami +1Gaussian ProcessesMulticlass Classification

    Department of Computer Science, University of Helsinki, Finland

  7. Kriging via variably scaled kernels

    Mar 16, 2026Gianluca Audone, Francesco Marchetti, Emma Perracchione +1Gaussian ProcessesGaussian Process Regression

    Faculty of Engineering and Physical Sciences, University of Southampton, United Kindom · Dipartimento di Matematica “Tullio Levi-Civita”, Universit`a di Padova, Italy · Dipartimento di Scienze Matematiche Giuseppe Luigi Lagrange, Politecnico di Torino, Italy +1

  8. GGMPs: Generalized Gaussian Mixture Processes

    Mar 11, 2026Vardaan Tekriwal, Mark D. Risser, Hengrui Luo +1Conditional Distribution EstimationGaussian Processes

    Applied Math & Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA · Department of Electrical Engineering & Computer Sciences, University of California, Berkeley, CA · Engineering Mathematics & Statistics Division, University of California, Berkeley, CA +3

  9. Posterior Sampling Reinforcement Learning with Gaussian Processes for Continuous Control: Sublinear Regret Bounds for Unbounded State Spaces

    Mar 9, 2026Hamish Flynn, Joe Watson, Ingmar Posner +1RL ControlRegret Minimization in RL

    Carnegie Mellon University · University of Oxford · Technical University of Darmstadt +2

  10. A Distributed Gaussian Process Model for Multi-Robot Mapping

    Mar 7, 2026Seth Nabarro, Mark van der Wilk, Andrew J. DavisonSparse Gaussian ProcessesGaussian Belief Propagation

    Dyson Robotics Lab, Imperial College London · Department of Computer Science, University of Oxford

  11. Structured Multitask Gaussian Processes for Probabilistic Full-Body Human Motion Prediction

    Mar 7, 2026Jinger Chong, Xiaotong Zhang, Kamal Youcef-ToumiHuman Motion PredictionGaussian Processes

    Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.

  12. Probabilistic Learning and Generation in Deep Sequence Models

    Mar 1, 2026Wenlong ChenBayesian InferenceSequence Modeling

    Imperial College London Department of Computing

  13. Scalable Gaussian process modeling of parametrized spatio-temporal fields

    Feb 27, 2026Srinath Dama, Prasanth B. NairGaussian ProcessesGaussian Process Regression

    University of Toronto Institute for Aerospace Studies, 4925 Dufferin Street, Toronto, M3H 5T6, Ontario, Canada

  14. Regular Fourier Features for Nonstationary Gaussian Processes

    Feb 26, 2026Arsalan Jawaid, Abdullah Karatas, Jörg SeewigFourier Feature EmbeddingsGaussian Processes

    Institute of Measurement and Sensor Technology, University of Kaiserslautern-Landau, Kaiserslautern, Germany · Independent Researcher, Mannheim, Germany

  15. From Shallow Bayesian Neural Networks to Gaussian Processes: General Convergence, Identifiability and Scalable Inference

    Feb 26, 2026Gracielle Antunes de Araújo, Flávio B. GonçalvesNyström MethodBayesian Neural Networks

    Universidade do Estado de Minas Gerais (UEMG), FaEnge – Faculdade de Engenharia. · Universidade Federal de Minas Gerais (UFMG), ICEx – Instituto de Ciências Exatas.

  16. Quasi-Periodic Gaussian Process Predictive Iterative Learning Control

    Feb 20, 2026Unnati Nigam, Radhendushka Srivastava, Faezeh Marzbanrad +1Iterative Learning ControlRobotic Control

    IITB-Monash Research Academy, IIT Bombay, Mumbai, India · Department of Mathematics, IIT Bombay, Mumbai, India · Department of Electrical and Computer Systems Engineering, Monash University, Clayton, Melbourne, Australia

  17. Distributed Quantum Gaussian Processes for Multi-Agent Systems

    Feb 16, 2026Meet Gandhi, George P. KontoudisGaussian ProcessesQuantum Machine Learning

    Colorado School of Mines, Golden, USA

  18. Frequentist Regret Analysis of Gaussian Process Thompson Sampling via Fractional Posteriors

    Feb 16, 2026Somjit Roy, Prateek Jaiswal, Anirban Bhattacharya +2Gaussian Process BanditsThompson Sampling

    Department of Statistics, Texas A&M University, College Station, TX 77843, USA · Daniels School of Business, Purdue University, West Lafayette, IN 47907, USA · Department of Statistics, University of Wisconsin-Madison, Madison, WI 53706, USA

  19. Improving Forecasts of Suicide Attempts for Patients with Little Data

    Nov 22, 2025Genesis Hang, Annie Chen, Hope Neveux +2Latent Variable ModelsGaussian Processes

    Wellesley College · Harvard University

  20. Warm-Starting Iterative Gaussian Processes for Faster Sequential Inference

    Nov 20, 2025Alan Yufei Dong, Jihao Andreas Lin, José Miguel Hernández-LobatoEfficient InferenceGaussian Processes

    Department of Engineering, University of Cambridge

  21. Deep Jump Gaussian Processes for Surrogate Modeling of High-Dimensional Piecewise Continuous Functions

    Oct 24, 2025Yang Xu, Chiwoo ParkDeep Gaussian ProcessesSurrogate Modeling

    Industrial & Systems Engineering, University of Washington, Seattle, WA, USA

  22. MAGIC: Multi-task Gaussian process for joint imputation and classification in healthcare time series

    Sep 23, 2025Dohyun Ku, Catherine D. Chong, Visar Berisha +2Time Series ImputationTime Series Classification

    H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, GA, USA · Department of Neurology, Mayo Clinic Arizona, AZ, USA · College of Health Solutions and School of Electrical Computer and Energy Engineering, Arizona State University, AZ, USA

  23. Gaussian Processes and Reproducing Kernel Hilbert Spaces: Connections and Equivalences

    Jun 20, 2025Motonobu Kanagawa, Philipp Hennig, Dino Sejdinovic +1Gaussian ProcessesReproducing Kernel Hilbert Spaces

    EURECOM · University of Tübingen, Tübingen AI Center Max Planck Institute for Intelligent Systems · Adelaide University Australian Institute for Machine Learning +1

  24. Spectral structure learning for clinical time series

    Feb 17, 2025Ivan Lerner, Anita Burgun, Francis BachMulti-Output Gaussian ProcessesTime-Series Causal Discovery

    Université Paris Cité, Inria, Inserm, HeKA, F-75015 Paris, France · Service d’informatique biomédicale, AP-HP, Hôpital Georges Pompidou, F-75015 Paris, France · SIERRA, Inria Paris, F-75015 Paris, France

  25. Second Maximum of a Gaussian Random Field and Exact (t-)Spacing test

    Jun 26, 2024Jean-Marc Azaïs, Federico Dalmao, Yohann De CastroStatistical Hypothesis TestingSparse Recovery

    Institut de Mathématiques de Toulouse Université Paul Sabatier, France · DMEL, CENUR Litoral Norte Universidad de la República, Salto, Uruguay · Institut Camille Jordan, CNRS UMR 5208 École Centrale Lyon, France +1