Reliable Uncertainty Quantification

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Predictive UncertaintyEpistemic UncertaintyUncertainty-Aware InferenceInput UncertaintiesCalibrated UncertaintyEpistemic StanceReducible Uncertainty

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Period ending 2026-09-21

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Period ending 2026-09-07

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  1. Dirichlet-Based Monte Carlo Dropout for Uncertainty Estimation in Neural Networks

    May 22, 2026Rouaa Hoblos, Noura Dridi, Noureddine Zerhouni +1Reliable Uncertainty QuantificationBayesian Neural Networks

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

    May 15, 2026Ruirui Liu, Xuejie Hou, Yiping Jiang +1Reliable Uncertainty QuantificationConditional-Value-At-Risk

  3. Inducing Artificial Uncertainty in Language Models

    May 13, 2026Sophia Hager, Simon Zeng, Nicholas AndrewsLarge Language Model UncertaintyReliable Uncertainty Quantification

  4. Online Conformal Prediction: Enforcing monotonicity via Online Optimization

    May 12, 2026Eduardo Ochoa Rivera, Ambuj TewariConformal PredictionQuantile Regression

  5. Self-Supervised Laplace Approximation for Bayesian Uncertainty Quantification

    May 12, 2026Julian Rodemann, Alexander Marquard, Thomas Augustin +1Bayesian Neural NetworksBayesian

  6. Foundations of Reliable Inference: Reliability-Efficiency Co-Design

    May 11, 2026Jiayi HuangReliable Uncertainty QuantificationBayesian

  7. On Uniform Error Bounds for Kernel Regression under Non-Gaussian Noise

    May 10, 2026Johannes Teutsch, Oleksii Molodchyk, Marion Leibold +2Reliable Uncertainty Quantification

  8. Asymptotically Log-Optimal Bayes-Assisted Confidence Sequences for Bounded Means

    May 8, 2026Valentin Kilian, Stefano Cortinovis, François CaronConfidence IntervalsBayesian

  9. Robust and Reliable AI for Predictive Quality in Semiconductor Materials Manufacturing with MLOps and Uncertainty Quantification

    May 8, 2026Min Gao, Julia Maria Perathoner, Anton Ludwig Bonin +2Semiconductor ManufacturingReliable Uncertainty Quantification

  10. Probabilistic Object Detection with Conformal Prediction

    May 8, 2026Christopher Ries, Moussa Kassem Sbeyti, Nicolas Bianco +1Conformal PredictionObject Detection

  11. Implicit Multi-Camera System Calibration Using Gaussian Processes

    May 8, 2026Ivan De Boi, Bart Ribbens, Veronika Golanova +2Camera IntrinsicsGaussian Process

  12. Estimating the Black-box LLM Uncertainty with Distribution-Aligned Adversarial Distillation

    May 7, 2026Huizi Cui, Huan Ma, Qilin Wang +2Large Language Model UncertaintyReliable Uncertainty Quantification

  13. Query2Uncertainty: Robust Uncertainty Quantification and Calibration for 3D Object Detection under Distribution Shift

    May 6, 2026Till Beemelmanns, Alexey Nekrasov, Stefan Vilceanu +43D Object DetectionCalibrated Uncertainty

  14. Quantile-Free Uncertainty Quantification in Graph Neural Networks

    May 6, 2026Soyoung park, Hwanjun Song, Sungsu LimReliable Uncertainty QuantificationGraph Neural Networks

  15. Gradients with Respect to Semantics Preserving Embeddings Tell the Uncertainty of Large Language Models

    May 6, 2026Mingda Li, Rundong Lv, Xinyu Li +2Large Language Model UncertaintyLarge Language Model Generation

  16. Amortized Variational Inference for Joint Posterior and Predictive Distributions in Bayesian Uncertainty Quantification

    May 5, 2026Nan Feng, Xun HuanVariational InferencePosterior

  17. LLM-XTM: Enhancing Cross-Lingual Topic Models with Large Language Models

    May 5, 2026Minh Chu Xuan, Tien-Phat Nguyen, Linh Ngo Van +3Topic ModelingLarge Language Model Adaptation

  18. Conformalized Quantum DeepONet Ensembles: Towards Scalable Operator Learning with Distribution-Free Guarantees

    May 1, 2026Purav Matlia, Christian Moya, Guang LinQuantum Neural NetworksProbabilistic Operator Learning

  19. Uncertainty Quantification for LLM Function-Calling

    Apr 24, 2026Zihuiwen Ye, Lukas Aichberger, Michael Kirchhof +5Large Language Model UncertaintyReliable Uncertainty Quantification

  20. Fast Bayesian equipment condition monitoring via simulation based inference: applications to heat exchanger health

    Apr 22, 2026Peter Collett, Alexander Johannes Stasik, Simone Casolo +1BayesianReliable Uncertainty Quantification

  21. Online Conformal Prediction with Adversarial Semi-bandit Feedback via Regret Minimization

    Apr 20, 2026Junyoung Yang, Kyungmin Kim, Sangdon ParkConformal PredictionFinite-Sample Coverage Guarantees

  22. Reference-state System Reliability method for scalable uncertainty quantification of coherent systems

    Apr 18, 2026Ji-Eun Byun, Hyeuk Ryu, Junho SongReliable Uncertainty QuantificationMonte Carlo

  23. MADE: A Living Benchmark for Multi-Label Text Classification with Uncertainty Quantification of Medical Device Adverse Events

    Apr 16, 2026Raunak Agarwal, Markus Wenzel, Simon Baur +3Multi-Label ClassificationDiagnostic Benchmark

  24. An Isotropic Approach to Efficient Uncertainty Quantification with Gradient Norms

    Mar 31, 2026Nils Grünefeld, Jes Frellsen, Christian HardmeierReliable Uncertainty QuantificationPredictive Uncertainty

  25. A plug-and-play approach with fast uncertainty quantification for weak lensing mass mapping

    Mar 23, 2026Hubert Leterme, Andreas Tersenov, Jalal Fadili +1CosmologyMapping

  26. Optimal uncertainty bounds for multivariate kernel regression under bounded noise: A Gaussian process-based dual function

    Mar 17, 2026Amon Lahr, Anna Scampicchio, Johannes Köhler +1Gaussian ProcessKernel Hilbert Spaces

  27. Volumetric Directional Diffusion: Anchoring Uncertainty Quantification in Anatomical Consensus for Ambiguous Medical Image Segmentation

    Mar 4, 2026Chao Wu, Mahesh Bhosale, Kangxian Xie +3Medical Image Segmentation3D Latent Diffusion Model

  28. Pixelwise Uncertainty Quantification of Accelerated MRI Reconstruction

    Jan 19, 2026Ilias I. Giannakopoulos, Lokesh B Gautham Muthukumar, Yvonne W. Lui +1Magnetic Resonance Imaging ReconstructionMagnetic Resonance Imaging

  29. Uncertainty Quantification for Regression: A Unified Framework based on kernel scores

    Oct 29, 2025Christopher Bülte, Yusuf Sale, Gitta Kutyniok +1Reliable Uncertainty QuantificationOut-Of-Distribution

  30. Toward Efficient Uncertainty in LLMs through Evidential Knowledge Distillation

    Jul 24, 2025Lakshmana Sri Harsha Nemani, P. K. Srijith, Tomasz KuśmierczykLarge Language Model UncertaintyKnowledge Distillation

  31. CLEAR: Calibrated Learning for Epistemic and Aleatoric Risk

    Jul 10, 2025Ilia Azizi, Juraj Bodik, Jakob Heiss +1Reliable Uncertainty QuantificationQuantile Regression

  32. Representation Learning for Equivariant Inference with Guarantees

    May 26, 2025Daniel Ordoñez-Apraez, Vladimir Kostić, Alek Fröhlich +3EquivarianceGeometric Deep Learning

  33. An Axiomatic Assessment of Entropy- and Variance-based Uncertainty Quantification in Regression

    Apr 25, 2025Christopher Bülte, Yusuf Sale, Timo Löhr +3Reliable Uncertainty QuantificationEpistemic Uncertainty

  34. From Uncertain to Safe: Conformal Adaptation of Diffusion Models for Safe PDE Control

    Feb 4, 2025Peiyan Hu, Xiaowei Qian, Wenhao Deng +8Reliable Uncertainty QuantificationConformal Calibration

  35. Voxeland: Probabilistic Instance-Aware Semantic Mapping with Evidence-based Uncertainty Quantification

    Nov 13, 2024Jose-Luis Matez-Bandera, Pepe Ojeda, Javier Monroy +2Semantic MappingDense Semantic Segmentation

  36. Uncertainty Quantification in Machine Learning for Biosignal Applications -- A Review

    Nov 15, 2023Ivo Pascal de Jong, Andreea Ioana Sburlea, Matias Valdenegro-ToroMultimodal Physiological SignalsReliable Uncertainty Quantification

  37. Distribution-Free Uncertainty Quantification for Kernel Methods by Gradient Perturbations

    Dec 23, 2018Balázs Csanád Csáji, Krisztián Balázs KisReliable Uncertainty QuantificationKernel Method

  38. Statistical Uncertainty Quantification for Aggregate Performance Metrics in Machine Learning Benchmarks

    Date pendingRachel Longjohn, Giri Gopalan, Emily CasletonReliable Uncertainty QuantificationEvaluation Metrics

  39. ActMap: Single-Pass Uncertainty Quantification from Generation-Time Activation Maps

    Date pendingJacopo Dardini (University of Bologna), Roberta Calegari (University of Bologna)Large Language Model UncertaintyEtsi-Compliant Class Activation Map