Density Estimation

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Overview

Density estimation seeks to describe how probability is distributed across possible observations, which supports tasks such as anomaly detection, forecasting, scientific inference, and data generation. Approaches range from kernel density estimation and Gaussian mixtures to copulas, probabilistic circuits, normalizing flows, and diffusion or energy-based models. Researchers also develop conditional and discrete estimators, with guarantees studied through measures such as likelihood, Hellinger distance, and total variation, including in high-dimensional and privacy-constrained settings. A central challenge is balancing flexible models and accurate density estimates with tractable computation, reliable uncertainty, and performance when data are sparse, shifted, or concentrated on lower-dimensional structure.

Latest papers

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67 papers14 papers in the last four weeks, up 133% on the four weeks before. 0.1% of all new papers.

  1. Vision-Based Density Estimation for Adaptive Traffic Control

    Oct 28, 2026Mohammad Usaid, Deepak Silaych, Hrithik Mhatre +1Traffic Flow EstimationTraffic Signal Control

    Department of Civil Engineering, Indian Institute of Technology Bombay · Department of Computer Science and Engineering, University of California San Diego

  2. An end-to-end framework for uncertainty-aware validation of generative models

    Oct 27, 2026Giada Badaracco, Sean Benevedes, Christina Reissel +2Uncertainty QuantificationGenerative Modeling

    ETH Zürich, Zürich, CH · NSF AI Institute for Artificial Intelligence and Fundamental Interactions, Cambridge, MA, USA · School of Physics, Georgia Institute of Technology, Atlanta, GA, USA +2

  3. Approximation Families and the Statistical Efficiency of Denoising Score Matching

    Oct 26, 2026Brian MiyatakeScore MatchingScore-Based Generative Modeling

    Department of Statistics and Data Science, Yale University

  4. Compatible Likelihoods for Flow Matching on Manifolds

    Oct 22, 2026Lucas Ng, Georgios Batzolis, Mark GirolamiFlow MatchingRiemannian Flow Matching

    University of Cambridge · Devotion AI Labs Ltd.

  5. How Many, but How Sure? Class Competition as a Confidence Proxy in Multi-Class Density-Based Counting

    Oct 16, 2026Villanelle O'Reilly, Georgios Leontidis, Marc HanheideCrowd CountingConfidence Estimation

    Lincoln Centre for Autonomous Systems, University of Lincoln, UK · Applied Vision and Artificial Intelligence Lab, University of Lincoln, UK · UiT The Arctic University of Norway, Norway

  6. Efficient Agnostic Learning of Univariate Densities Under Local Differential Privacy

    Oct 15, 2026Mohammad Afzali, Hassan Ashtiani, Sivan SabatoDifferential PrivacyDensity Estimation

    University of British Columbia · McMaster University · Vector Institute +1

  7. Real-Time Traffic Density Estimation: A Hybrid Computer Vision and Predictive Machine Learning Pipeline

    Oct 9, 2026Prince Kwabena Appiah BoaduDensity EstimationTraffic Flow Estimation

    Department of Computer Engineering, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

  8. Symbolic Density Estimators for Unnormalized Distributions

    Oct 7, 2026Vikas Kanaujia, Riyansha Singh, Shashank Sharma +1Density EstimationSymbolic Regression

    Department of Electrical Engineering IIT Kanpur · Department of Computer Science and Engineering IIT Kanpur · Department of Physics IIT Kanpur +1

  9. Gaussian Density Splatting Network

    Oct 7, 2026Miao Shang, Yabin Wang, Xiaopeng HongCrowd CountingDensity Estimation

    Faculty of Computing Harbin Institute of Technology

  10. The Silhouette Operator: Identifiability of Low-Rank Measures from One-Dimensional Projections

    Oct 7, 2026Robert A. VandermeulenQuery IdentifiabilityDensity Estimation

  11. Scalable Logistic Gaussian Process Density Regression with Kinetic Langevin Sampling

    Oct 7, 2026Daniel Paulin, Ádám Jung, András A. BenczúrConditional Distribution EstimationDensity Estimation

    Nanyang Technological University · Eötvös Lor´and University (ELTE) HUN-REN Institute for Computer Science and Control (SZTAKI)

  12. Uniform Discrete Diffusion Models are Minimax Optimal for Estimating Distributions with Small Effective Support Size

    Oct 6, 2026Dongsun Yoon, Saptarshi ChakrabortyMinimax EstimationStatistical Learning Theory

    Department of Statistics, University of Michigan

  13. Polylogarithmic Sparsity of Randomly Reweighted NPMLEs for Gaussian Mixtures

    Oct 1, 2026Hansheng JiangGaussian Mixture ModelsDensity Estimation

    University of Toronto

  14. BayesNDE: Bayesian Generative Modeling for Neural Density Estimation

    Sep 30, 2026Chenglin Li, Qiao LiuGenerative ModelingDensity Estimation

    Department of Biostatistics, Yale University New Haven, Connecticut, USA

  15. Learning the Structure of Triangular Transport Maps

    Sep 29, 2026Morten Blørstad, Pekka Parviainen, Berent Ånund Strømnes LundeFlow Map LearningDensity Estimation

    Department of Informatics, University of Bergen · Equinor

  16. VesselBench-800K: A Large-scale Perception Benchmark for Multimodal Vessel Detection, Counting, and Density Estimation

    Sep 29, 2026Danfeng Hong, Chenyu Li, Jocelyn ChanussotObject CountingRemote Sensing

    School of Automation, Southeast University, Nanjing 211189, China · Univ. Grenoble Alpes, INRAE, LESSEM, 38000 Grenoble, France · Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP, LJK, Grenoble 38000, France

  17. From Data to Program: Fast & Direct Generative Program Inference from Empirical Data

    Sep 28, 2026Simon Klüttermann, Xueying Ding, Leman AkogluProgram SynthesisSynthetic Tabular Data Generation

    Carnegie Mellon University

  18. Discrete Diffusion Models via Evolving Variational Autoregressive Networks

    Sep 23, 2026Kewen Pan, Ying TangDiffusion SamplingDensity Estimation

    Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China · School of Physics, University of Electronic Science and Technology of China, Chengdu 611731, China · Key Laboratory of Quantum Physics and Photonic Quantum Information, Ministry of Education, University of Electronic Science and Technology of China, Chengdu 611731, China +1

  19. SAFe: Segment-guided Aggregation of Feature Densities for Anomaly-aware Segmentation

    Sep 21, 2026Anja Delić, Jurica Runtas, Marin Oršić +2Anomaly LocalizationDensity Estimation

    University of Zagreb Faculty of Electrical Engineering and Computing Laboratory for Autonomous Systems and Mobile Robotics Zagreb, Croatia

  20. A Splitting Method for SDE Terminal-Law Estimation

    Sep 11, 2026Rushil Gupta, Sandeep JunejaStochastic Differential EquationsDiffusion Model Sampling

    Safexpress Centre for Data, Learning and Decision Sciences Ashoka University

  21. Closed-Form of the Local Galactic Potential and Stellar Distribution Function from Gaia DR3

    Sep 8, 2026Indranil Das, Adam Kamoski, Dora Demiri +3Density Estimation

    Department of Physics University of Massachusetts Boston NSF Institute for AI and Fundamental Interactions · Lebedev Physical Institute Russian Academy of Sciences Moscow 119991, Russia

  22. Source Distribution Estimation by Posterior Averaging

    Sep 2, 2026Trung-Dung Hoang, Lisa M. KochSimulation-Based InferenceDensity Estimation

    Department of Digital Medicine, University of Bern, Switzerland · Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism UDEM, Inselspital, Bern University Hospital, University of Bern, Switzerland · Graduate School for Cellular and Biomedical Sciences (GCB), University of Bern, Switzerland +1

  23. Minimax bounds for watermarked and masked recursive discrete distribution estimation

    Aug 31, 2026Millen Kanabar, Michael GastparDataset WatermarkingMinimax Estimation

    School of Computer and Communication Sciences, EPFL, Switzerland

  24. Amortized Bandwidth Learning for Kernel Density Estimation under Logarithmic Score

    Aug 20, 2026Junyi Liang, Hailiang DuDensity EstimationKernel Density Estimation

    School of Mathematics, East China University of Science and Technology, 200237 Shanghai, China · Department of Mathematical Sciences; Institute of Hazard, Risk and Resilience, Durham University, DH1 3LE Durham, United Kingdom · Data Science Institute; Global School of Sustainability, The London School of Economics and Political Science, WC2A 2AE London, United Kingdom

  25. Wasserstein Filtering: A Sample Selection Method for Robust Distribution Learning

    Aug 13, 2026Yikai Xu, Zhao Chen, Jian HuangUnsupervised Anomaly DetectionDensity Estimation

    Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong, China. · School of Data Science, Fudan University, Shanghai, China. · Department of Data Science and Artificial Intelligence, and Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong, China.

  26. In-Context Density Estimation for Tabular Data

    Aug 10, 2026Patryk Marszałek, Jacek Tabor, Marek ŚmiejaEnergy-Based ModelsUnsupervised Anomaly Detection

    Faculty of Mathematics and Computer Science, Jagiellonian University, Kraków, Poland

  27. Inverse Learning of Latent Risk-Neutral Densities from Irregular Option Quotes

    Jul 29, 2026Lennon J. Shikhman, Michael Galarnyk, Aadi Dash +1Quantitative FinanceDeep Operator Networks

    College of Computing, Georgia Institute of Technology, USA · College of Engineering, Georgia Institute of Technology, USA · Department of Mathematics and Systems Engineering, Florida Institute of Technology, USA

  28. Breaking the Curse with BAND: Nonparametric Distribution Estimation in High Dimensions

    Jul 29, 2026Shuo-Chieh Huang, Chien-Ming Chi, Jau-er ChenBayesian NetworksDensity Estimation

    Department of Statistics, Rutgers University, Piscataway, NJ, U.S.A. · Institute of Statistical Science, Academia Sinica, Taipei, Taiwan · School of Political Science and Economics, National Taiwan University, Taipei, Taiwan

  29. Localized Anomaly Detection via Differentiable D-vine Copulas

    Jul 27, 2026Nicholas Andrea Pearson, Francesca Zanello, Davide Russo +2Anomaly LocalizationDensity Estimation

    University of Trieste, Trieste, Italy · Idrostudi srl, Trieste, Italy

  30. The Hyperspherical Geometry of CLIP Latent Space: A Semantic Mixture Model

    Jul 15, 2026Zijie Yu, Gaowen Liu, Ramana Rao Kompella +2Latent Variable ModelsHyperspherical Representation Learning

    Tsinghua University · Cisco Research · University of Illinois Chicago