Uncertainty Propagation

Ask about this topic

Overview

Uncertainty propagation asks how uncertain inputs, parameters, and model predictions affect later calculations, forecasts, and decisions. Common approaches include linearization and the delta method, Monte Carlo sampling, Bayesian models, interval bounds, and learned probabilistic surrogates that carry distributions or covariances through complex systems. Applications range from scientific simulations and medical measurements to robotics and multi-stage AI systems, where benchmarks often assess calibration, coverage, sharpness, and downstream risk. A central challenge is balancing computational cost and useful precision while preserving dependencies: separately calibrated components can still produce unreliable results when their uncertainties interact.

Latest papers

CardsList

44 papers4 papers in the last four weeks, up 33% on the four weeks before. 0.0% of all new papers.

  1. Diffusion Posterior Sampling with Uncertain Forward Models

    Oct 21, 2026Wentao Shangguan, Vivek K GoyalDiffusion-Based Inverse ProblemsDiffusion Posterior Sampling

    Department of Electrical and Computer Engineering, Boston University, Boston, MA 02215, USA

  2. Modeling Uncertainty Propagation in 3D Morphable Models

    Oct 17, 2026Megh Shukla, Edo Collins, Prashanth Chandran +4UQ for 3D ReconstructionUncertainty Propagation

    EPFL · Google · EPFL, Waabi

  3. Uncertainty Evaluation: Bridging Machine Learning and Measurement Science

    Oct 13, 2026Dario Petri, Luca MariUncertainty QuantificationUncertainty Decomposition

    Department of Industrial Engineering of the Università di Trento, Trento, Italy · Department of Philosophy of the Università Cattolica di Milano, Milano, Italy

  4. Propagating Elevation-Map Uncertainty Through the Contact Maximum in Closed Form

    Oct 5, 2026Aleš Kučera, Karel ZimmermannUncertainty QuantificationSafe Motion Planning

    Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic

  5. Human-in-the-Loop Geospatial Annotation for Rapid Dataset Construction in Field-Deployed UAV Systems

    Sep 23, 2026Morgan Masters, Adam Korycki, Nikolaas Bender +4Human-in-the-Loop AnnotationUncertainty Propagation

    Department of Electrical and Computer Engineering, University of California Santa Cruz

  6. Marginal Calibration Does Not Compose: Hidden Dependence in Modular Robot Navigation

    Sep 20, 2026Rista BaralModular RoboticsRobot State Estimation

    University of Delaware

  7. Uncertainty-Aware Trajectory Forecasting from Imperfect Tracking

    Aug 31, 2026Stephane Da Silva Martins, Victor Petrovic, Emanuel Aldea +1Probabilistic Trajectory PredictionProbabilistic Forecasting

    SATIE – CNRS UMR 8029, Université Paris-Saclay, France · ENS Paris-Saclay, Université Paris-Saclay, France

  8. PropUQ-MAS: Propagation-Aware Uncertainty Quantification for LLM Multi-Agent Systems

    Aug 22, 2026Yaokun Liu, Yifan Liu, Daniel Yue Zhang +3Multi-Agent LLM SystemsLLM Uncertainty Estimation

    University of Illinois Urbana-Champaign · Scale AI

  9. Uncertainty propagation in auto-regressive random neural network models

    Aug 20, 2026Janice Adams, Daniele VenturiUncertainty PropagationUncertainty Quantification

    Department of Applied Mathematics, UC Santa Cruz, Santa Cruz, CA 95064

  10. From Sequence to Structure: Relational Uncertainty Propagation for LLM Agents

    Aug 17, 2026Zhengzhao Ma, Boxi Cao, Yaojie Lu +3LLM Uncertainty EstimationLLM Agent Reliability

    Chinese Information Processing Laboratory, Institute of Software, Chinese Academy of Sciences · University of Chinese Academy of Sciences, Beijing, China

  11. Sensor-Informed Per-Point Covariance for Structured-Light 3D Imaging

    Aug 11, 2026Sehoon Tak, Jae-Sang HyunFringe Projection ProfilometryUncertainty Quantification

    Department of Mechanical Engineering, Yonsei University, Seoul 03722, South Korea

  12. When Unpaired Sets Support Shared-Corruption Calibration: Moment Geometry and Two-Sample Precision

    Aug 11, 2026Shuheng Cao, Zhenhao Zhang, Ruiqi Chen +5Parameter IdentifiabilityUncertainty Propagation

    University of California, San Diego · ShanghaiTech University · Tsinghua University +4

  13. Structure-Preserving Uncertainty Propagation in First-Order Proof Search

    Aug 10, 2026Tanel TammetProbabilistic LogicLogical Reasoning

    Tallinn University of Technology

  14. Two-Step MV-DeepONet: Probabilistic Operator Learning for Uncertainty Propagation Driven by Random Input Fields

    Aug 10, 2026Yupei Nie, Lei Wang, Jiasen LiuUncertainty QuantificationPDE Surrogate Modeling

    School of Mathematics and Physics, North China Electric Power University, Beijing 102206, P.R. China · School of Energy Power and Mechanical Engineering, North China Electric Power University, Beijing 102206, P.R. China

  15. CUPA-T2*: Covariance-Aware Uncertainty Propagation and Alignment for T2* Mapping in Accelerated MRI

    Aug 9, 2026Gideon N. L. Rouwendaal, Natascha Niessen, Hannah Eichhorn +3Uncertainty QuantificationHeteroscedastic Regression

    Institute of Machine Learning in Biomedical Imaging, Helmholtz Munich, Germany · School of Computation, Information & Technology, Technical University of Munich, Germany · GE HealthCare, Munich, Germany +6

  16. PPDL: LLM-Based Flows as Probabilistic Programs

    Aug 5, 2026Louis Mandel, Guillaume Baudart, Mandana Vaziri +1LLM InferenceLLM Reliability

    IBM, New York, USA · Université Paris Cité, Inria, CNRS, IRIF, France

  17. Runtime Uncertainty Monitoring for LLM-Based Multi-Agent Systems Using Bayesian Networks

    Jul 28, 2026Bart Custers, Koorosh AslansefatMulti-Agent LLM SystemsUncertainty Quantification

    University of Hull, Hull HU6 7RX, UK

  18. Interval and fuzzy physics-augmented neural networks (iPANN and fPANN) for uncertainty quantification and propagation in constitutive modeling

    Jul 22, 2026Somesh Pratap Singh, Govinda Anantha Padmanabha, Jingye Tan +4Uncertainty QuantificationHyperelasticity

    Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, 14853, NY, USA · Ecole Polytechnique Federale de Lausanne (EPFL), 1015, Lausanne, Switzerland · Department of Aerospace and Mechanical Engineering, University of Southern California, Los Angeles, 90007, CA, USA +2

  19. Bayesian Uncertainty Propagation for Agentic RAG Pipelines: A Proof-of-Concept Study on Multi-Hop Question Answering

    Jul 1, 2026Louis Donaldson, Connor Walker, Koorosh Aslansefat +1Uncertainty QuantificationAgentic RAG

    University of Hull, Hull HU6 7RX, UK

  20. YUKTI: From Natural-Language Situations to Robust, Verifiable Decisions An Uncertainty-Typed Proposition IR, Assumption-Robust Pareto Frontiers, and a Regret Certificate

    Jun 22, 2026Suyash MishraLarge Language Model-Guided OptimizationRobust Optimization

    AI Researcher

  21. Continuous-Time Probabilistic Correctors for Uncertainty-Aware Physics-Based Spacecraft Trajectory Forecasting

    Jun 19, 2026Muhammad Bilal Shahid, Zhanhong Jiang, Soumik Sarkar +1Neural Controlled Differential EquationsUncertainty Quantification

    Iowa State University, Ames, Iowa, 50011, USA

  22. Calibrated Sampling-Free Uncertainty Estimation in Bayesian Deep Learning

    Jun 15, 2026Tobias Jan Wieczorek, Leon de Andrade, Thomas Möllenhoff +1Bayesian Neural NetworksUncertainty Quantification

    TU Darmstadt & hessian.AI, Darmstadt, Germany · RIKEN Center for Advanced Intelligence Project, Tokyo, Japan

  23. Confidence Laundering in Agent Systems: Why Uncertainty Needs a Latent Carrier

    Jun 9, 2026Kaiwen Shi, Zheyuan Zhang, Han Bao +2Agent ReliabilityUncertainty Quantification

    University of Notre Dame

  24. A practical probabilistic framework for deformable image registration uncertainty in radiotherapy dose propagation

    Jun 8, 2026Stefan Heldmann, Sven Kuckertz, Nasim Givehchi +4Uncertainty QuantificationOncology

    Fraunhofer Institute for Digital Medicine MEVIS, Lübeck, Germany · Varian, a Siemens Healthineers company, Dättwil, Switzerland · Icon Group, South Brisbane, QLD, Australia

  25. Uncertainty-Calibrated Diffusion for Reliable 3D Molecular Graph Generation

    Jun 1, 2026Fang Wan, Jingxiang Qu, Yi LiuDiffusion SamplingMolecular Graph Generation

    State University of New York at Stony Brook

  26. Decomposing Ensemble Spread in Lorenz '96 With Learned Stochastic Parameterizations

    May 21, 2026Birgit Kühbacher, Daan Crommelin, Niki KilbertusUncertainty QuantificationChaotic Dynamical Systems

    Technical University of Munich, Munich, Germany · Helmholtz Munich, Munich, Germany · Munich Center for Machine Learning (MCML), Munich, Germany +2

  27. Improving Spatio-Temporal Residual Error Propagation by Mitigating Over-Squashing

    May 18, 2026Seyed Mohamad Moghadas, Esther Rodrigo Bonet, Bruno Cornelis +1Graph RewiringOver-Squashing

    ETRO Department, Vrije Universiteit Brussel, B-1050 Brussels, Belgium · imec Kapeldreef 75, B-3001 Leuven, Belgium

  28. A numerical study into neural network surrogate model performance for uncertainty propagation

    May 15, 2026Noah Wade, Kirubel TeferraNeural Surrogate ModelingUncertainty Quantification

    ASEE Postdoctoral Associate, U.S. Naval Research Laboratory, Washington, DC, 20375, USA · U.S. Naval Research Laboratory, Washington, 20375, DC, USA

  29. Learning Context-conditioned Gaussian Overbounds for Convolution-Based Uncertainty Propagation

    May 15, 2026Ruirui Liu, Xuejie Hou, Yiping Jiang +1Uncertainty QuantificationUncertainty Propagation

    Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, Hong Kong, China

  30. Heuristic Pathologies and Further Variance Reduction via Uncertainty Propagation in the AIVAT Family of Techniques

    May 14, 2026Juho Kim, Tuomas SandholmCounterfactual EvaluationUncertainty Quantification

    Computer Science Department Carnegie Mellon University