Covariance Estimation

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Overview

Covariance estimation studies how to recover the relationships and uncertainty among variables from finite, often noisy observations, supporting tasks such as scientific inference, portfolio design, sensor fusion, and machine learning. Classical approaches include shrinkage and low-rank models, while robust likelihoods, Bayesian methods, and expectation-maximization address outliers and missing data. Newer methods use online estimators and structured neural models to track changing covariance or represent large matrices efficiently, sometimes with privacy or stability guarantees. A central challenge is balancing accuracy and reliable uncertainty estimates against limited data, computational cost, distribution shifts, and privacy constraints.

Latest papers

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61 papers7 papers in the last four weeks, down 22% on the four weeks before. 0.0% of all new papers.

  1. Online Covariance Estimation for Averaged Stochastic Gradient Descent on Riemannian Manifolds

    Oct 24, 2026Jingrong Guan, Liwei Jiang, Sen NaCovariance EstimationRiemannian Optimization

    Department of Industrial Engineering and Management Sciences, Northwestern University · Edwardson School of Industrial Engineering, Purdue University · School of Industrial and Systems Engineering, Georgia Institute of Technology

  2. Federated Differentially Private Optimization via Low-Rank Preconditioning

    Oct 22, 2026Antti Koskela, Tejas Kulkarni, Elias RaninenDifferentially Private Federated LearningDifferential Privacy

    Nokia Bell Labs

  3. Robust Covariance Estimation for Entry-wise Contaminated and Partially Observed Data via Expectation Maximization Algorithm

    Oct 15, 2026Matys Savidan, Mohammed Nabil El KorsoCovariance EstimationExpectation-Maximization

    ENS Paris-Saclay, France · Paris Saclay University, France

  4. SCORE: Spectral Correlation Estimation for Multivariate Gaussians

    Oct 8, 2026Christopher Bülte, Emil Partow, Astha Gupta +2Covariance Estimation

    LMU Munich · Munich Center for Machine Learning (MCML) · DLR-German Aerospace Center +1

  5. Joint Precision Neural Networks: Task-Aware Dependency and Predictive Learning

    Oct 5, 2026Andrea Cavallo, Samuel Rey, Antonio G. Marques +1Graph Structure LearningGraph Neural Networks

    INSY Department, Delft University of Technology · Department of Signal Theory and Communications, King Juan Carlos University

  6. Inference for stochastic differential equations driven by weighted sub-fractional Brownian motion using neural networks and the Euler approximation

    Sep 30, 2026J. H. Ramirez-GonzalezParameter EstimationStochastic Differential Equations

    Institute of Mathematics and Statistics, University of São Paulo (IME–USP), São Paulo, Brazil

  7. Mean Spatial Frequency Decoupling for Learning-Based Uplink-to-Downlink Covariance Conversion in FDD Massive MIMO

    Sep 30, 2026Melih Can ZerinChannel EstimationCovariance Estimation

    Department of Electrical and Electronics Engineering Middle East Technical University Ankara, Türkiye

  8. PhiFold: Towards Dynamic Protein Design with Physics-Structured Covariance Modeling

    Sep 26, 2026Yutian Liu, Mujie Lin, LanqianZhang +4Protein DesignProtein Structure Generation

    School of Computer Science, Peking University, Beijing, China · School of Electronic and Computer Engineering, Peking University, Shenzhen, China · School of Life Sciences, Tsinghua University, Beijing 100084, China +2

  9. Spatiotemporal Kronecker Covariance Neural Networks

    Sep 21, 2026Andrea Cavallo, Athanasios Georgoutsos, Elvin IsufiMultivariate Time Series ForecastingTemporal GNNs

    Delft University of Technology, Delft, Netherlands

  10. Improved Private Sparse Covariance Estimation with Multiscale Threshold Tests

    Sep 19, 2026Zihan ZhangCovariance EstimationDifferential Privacy

    Department of CSE, HKUST

  11. Locally Private Inference for Riemannian Stochastic Optimization

    Sep 18, 2026Xiaotian Chang, Yangdi Jiang, Qirui HuRiemannian OptimizationConfidence Region Estimation

    School of Physical and Mathematical Sciences, Nanyang Technological University · School of Statistics and Data Science, Shanghai University of Finance and Economics.

  12. Online Algorithms for Independent Low-Rank Matrix Analysis and Rank-Constrained Spatial Covariance Matrix Estimation Based on Maximum Weighted Likelihood Estimation

    Sep 18, 2026Yuto Ishikawa, Norihiro Takamune, Tomohiko Nakamura +4Audio Source SeparationCovariance Estimation

    Graduate School of Information Science and Technology, The University of Tokyo, Tokyo 113-8656, Japan · National Institute of Technology, Kagawa College, Takamatsu, Kagawa 761-8058, Japan · Yamaha Corporation, Hamamatsu-shi, Shizuoka 430-8650, Japan

  13. A Closed-Form Estimator and Diagnostic Battery for Anchor-Judge Error Correlation, Under a Single-Common-Factor Model

    Sep 8, 2026Veerendra Kumar SunkavalliLatent Variable ModelsLLM-as-a-Judge

    Independent Researcher

  14. MAC-I2^2: Learned Metrics-Aware Covariance for Robust Visual-Inertial Fusion in Initialization and Calibration

    Sep 7, 2026Xiang Fei, Yuheng Qiu, Can Xu +5Multimodal Sensor FusionCovariance Estimation

    The Robotics Institute, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA 15213 USA. · University of Toronto Institute for Aerospace Studies (UTIAS), University of Toronto, 4925 Dufferin St, Toronto, ON M3H 5T6, Canada. · Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), Masdar City, Abu Dhabi, UAE.

  15. Diagonal Attenuation: A Finite-Sample Correction for PCA

    Sep 5, 2026Qiang SunPrincipal Component AnalysisCovariance Estimation

    University of Toronto and MBZUAI

  16. End-to-End Neural Shrinkage of Indefinite Pairwise Correlation Matrices for Small-Cap-Inclusive Portfolios

    Aug 31, 2026Christian Bongiorno, Lorenzo VillasseroQuantitative FinancePortfolio Optimization

    Université Paris-Saclay, CentraleSupélec · Mathématiques et Informatique pour la Complexité et les Systèmes · Gif-sur-Yvette, France +2

  17. It depends: Incorporating correlations for joint aleatoric and epistemic uncertainties of high-dimensional output spaces

    Aug 25, 2026Leonhard F. Feiner, Manuel Nickel, Martin Menten +6Uncertainty QuantificationUncertainty Decomposition

    AI in Medicine and Healthcare, Klinikum rechts der Isar, Technical University of Munich, Germany · Institute of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, Technical University of Munich, Germany · Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Germany +6

  18. Equivariant Covariance Tensors: Guaranteed SPD Uncertainty for Tensor-Valued Geometric Learning

    Aug 25, 2026Ruihan Liu, Yu Ji, Jianbo Yu +2Uncertainty QuantificationCovariance Estimation

    College of Intelligent Robotics and Advanced Manufacturing, Fudan University, Shanghai 200433, China · School of Microelectronics, Fudan University, Shanghai 200433, China · ByteDance, Beijing, China +1

  19. Spectral Pre-Filtering for Context-Adaptive Sensor Fusion: A Four-Role FFT-GDCB Integration for High-Stakes Decision Systems

    Aug 22, 2026Oleg MiroshnichenkoKalman FilteringCovariance Estimation

  20. Sparse Separable Factor Analysis in the Complex Domain with an Application to Local Field Potential Data

    Aug 21, 2026Ian Hultman, Kirtikanth Kalapatapu, Yassine Filali +2Covariance EstimationMatrix Factorization

    Department of Statistics and Actuarial Science, University of Iowa · Department of Molecular Physiology and Biophysics, University of Iowa

  21. Unscented KalmanNet: Structure-Preserving Deep Learning with Calibrated Posterior Uncertainty under Incomplete Physics and Unknown Noise

    Aug 4, 2026Minhyeok Ko, Abdollah ShafieezadehKalman FilteringUnscented Kalman Filtering

    Department of Civil and Construction Engineering and Management, The University of Texas at Tyler, Tyler, TX, 75799, USA · Department of Civil, Environmental, and Geodetic Engineering, The Ohio State University, Columbus, OH, 43210, USA

  22. Deep Shape Regression for Planar Curves with Multimodal Covariates

    Jul 21, 2026Manuel Pfeuffer, Roshan Prakash Rane, Hadya Yassin +2Statistical Shape ModelingCovariance Estimation

    Humboldt-Universität zu Berlin, Berlin, Germany · Hertie Institute for AI in Brain Health, Universität Tübingen, Tübingen, Germany · Universität Tübingen, Tübingen, Germany +1

  23. Adaptive MPPI with Online Disturbance Covariance Estimation: Provable Stability Tightening via Spatial Smoothing

    Jul 9, 2026Hyung-Jin Yoon, Hunmin KimLyapunov StabilityStochastic Approximation

    Department of Mechanical and Nuclear Engineering, Tennessee Technological University, Cookeville, TN, USA

  24. Analyzing Uncertainty in the Spatial Representation of the Kinematic Bicycle Model

    Jun 28, 2026Shafayat Abrar, M. Zaeem Baig, Shahir Ul Islam Anzal +1Uncertainty QuantificationCovariance Estimation

    Dhanani School of Science and Engineering Habib University, Karachi 75290

  25. The Decision Geometry of Covariance Estimation for the Global Minimum-Variance Portfolio under Heavy Tails

    Jun 25, 2026Xavier FonsecaRegret MinimizationPortfolio Optimization

    Academy for AI, Games and Media, Breda University of Applied Sciences, Breda, The Netherlands.

  26. SOAP-Bubbles: Structured Weight Uncertainty for Neural Networks

    Jun 22, 2026Adrian Robert Minut, Nico Daheim, Marco Miani +3Bayesian Neural NetworksNeural Posterior Estimation

    Sapienza University of Rome, Rome, Italy · Ubiquitous Knowledge Processing Lab (UKP Lab), Department of Computer Science, Technical University of Darmstadt · Technical University of Denmark, Lyngby, Denmark +3

  27. On the Curse of Dimensionality in Private Sparse Covariance Estimation and PCA

    Jun 20, 2026Syamantak Kumar, Shourya Pandey, Purnamrita Sarkar +1Principal Component AnalysisMinimax Estimation

    University of Texas at Austin

  28. ARC: Adaptive Robust Joint State and Covariance Estimation

    Jun 18, 2026Alexandre Hadji-Thomas, Andrew Stirling, James R. ForbesCovariance EstimationRobot State Estimation

  29. Ablation, Statistical Inference, and Validation for KV-Cache Compression

    Jun 14, 2026Paolo D'Alberto, Ashish Siarasao, Elliott Delaye +1KV CachingRotation-Based Quantization

    Advanced Micro Devices, Inc.

  30. Covariance Shrinkage via Stochastic Interpolation

    Jun 5, 2026Mathieu Chalvidal, Florentin Coeurdoux, Eric Vanden-EijndenStochastic InterpolantsCovariance Estimation

    Capital Fund Management 23 Rue de l’Universit´e, 75007 Paris