{"total":92,"rows":[{"id":"2107.03342","title":"A Survey of Uncertainty in Deep Neural Networks","created":"2021-07-07","cited_by_count":680,"area":null},{"id":"2209.03302","title":"Quantifying Aleatoric and Epistemic Uncertainty in Machine Learning: Are Conditional Entropy and Mutual Information Appropriate Measures?","created":"2022-09-07","cited_by_count":125,"area":null},{"id":"2311.08718","title":"Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling","created":"2023-11-15","cited_by_count":114,"area":null},{"id":"2204.09308","title":"A Deeper Look into Aleatoric and Epistemic Uncertainty Disentanglement","created":"2022-04-20","cited_by_count":87,"area":null},{"id":"2210.03736","title":"Trustworthy clinical AI solutions: a unified review of uncertainty quantification in deep learning models for medical image analysis","created":"2022-10-05","cited_by_count":63,"area":null},{"id":"2312.00995","title":"Second-Order Uncertainty Quantification: A Distance-Based Approach","created":"2023-12-02","cited_by_count":35,"area":null},{"id":"2306.11113","title":"Learn to Accumulate Evidence from All Training Samples: Theory and Practice","created":"2023-06-19","cited_by_count":29,"area":null},{"id":"2307.03217","title":"Quantification of Uncertainty with Adversarial Models","created":"2023-07-06","cited_by_count":28,"area":null},{"id":"2104.14528","title":"GasHis-Transformer: A Multi-scale Visual Transformer Approach for Gastric Histopathological Image Detection","created":"2021-04-29","cited_by_count":26,"area":null},{"id":"2401.08501","title":"ValUES: A Framework for Systematic Validation of Uncertainty Estimation in Semantic Segmentation","created":"2024-01-16","cited_by_count":25,"area":null},{"id":"2406.02354","title":"Label-wise Aleatoric and Epistemic Uncertainty Quantification","created":"2024-06-04","cited_by_count":22,"area":null},{"id":"2404.12215","title":"Quantifying Aleatoric and Epistemic Uncertainty with Proper Scoring Rules","created":"2024-04-18","cited_by_count":21,"area":null},{"id":"2401.00276","title":"Second-Order Uncertainty Quantification: Variance-Based Measures","created":"2023-12-30","cited_by_count":19,"area":null},{"id":"2107.10384","title":"Ensemble-based Uncertainty Quantification: Bayesian versus Credal Inference","created":"2021-07-21","cited_by_count":16,"area":null},{"id":"2311.15451","title":"Uncertainty-aware Language Modeling for Selective Question Answering","created":"2023-11-26","cited_by_count":16,"area":null},{"id":"2405.15047","title":"Credal Wrapper of Model Averaging for Uncertainty Estimation in Classification","created":"2024-05-23","cited_by_count":13,"area":null},{"id":"2406.00332","title":"A Structured Review of Literature on Uncertainty in Machine Learning & Deep Learning","created":"2024-06-01","cited_by_count":10,"area":null},{"id":"2109.10702","title":"A Quantitative Comparison of Epistemic Uncertainty Maps Applied to Multi-Class Segmentation","created":"2021-09-22","cited_by_count":9,"area":null},{"id":"2112.02694","title":"Benchmark for Out-of-Distribution Detection in Deep Reinforcement Learning","created":"2021-12-05","cited_by_count":9,"area":null},{"id":"2401.09881","title":"GA-SmaAt-GNet: Generative Adversarial Small Attention GNet for Extreme Precipitation Nowcasting","created":"2024-01-18","cited_by_count":9,"area":null},{"id":"2408.00619","title":"Harnessing Uncertainty-aware Bounding Boxes for Unsupervised 3D Object Detection","created":"2024-08-01","cited_by_count":9,"area":null},{"id":"2412.07169","title":"Rate-In: Information-Driven Adaptive Dropout Rates for Improved Inference-Time Uncertainty Estimation","created":"2024-12-10","cited_by_count":7,"area":null},{"id":"2602.08470","title":"Learning Credal Ensembles via Distributionally Robust Optimization","created":"2026-02-09","cited_by_count":7,"area":null},{"id":"2108.11693","title":"Improving the Reliability of Semantic Segmentation of Medical Images by Uncertainty Modeling with Bayesian Deep Networks and Curriculum Learning","created":"2021-08-26","cited_by_count":6,"area":null},{"id":"2311.15816","title":"Scale-Dropout: Estimating Uncertainty in Deep Neural Networks Using Stochastic Scale","created":"2023-11-27","cited_by_count":6,"area":null},{"id":"2411.16370","title":"A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation","created":"2024-11-25","cited_by_count":6,"area":null},{"id":"2506.16589","title":"Spatially-Aware Evaluation of Segmentation Uncertainty","created":"2025-06-19","cited_by_count":6,"area":null},{"id":"2212.08123","title":"Bayesian posterior approximation with stochastic ensembles","created":"2022-12-15","cited_by_count":5,"area":null},{"id":"2403.17224","title":"Uncertainty Quantification for Gradient-based Explanations in Neural Networks","created":"2024-03-25","cited_by_count":5,"area":null},{"id":"2410.01628","title":"Stochasticity in Motion: An Information-Theoretic Approach to Trajectory Prediction","created":"2024-10-02","cited_by_count":5,"area":null},{"id":"2501.18268","title":"Reducing Aleatoric and Epistemic Uncertainty through Multi-modal Data Acquisition","created":"2025-01-30","cited_by_count":5,"area":null},{"id":"2107.07618","title":"Adversarial Attack for Uncertainty Estimation: Identifying Critical Regions in Neural Networks","created":"2021-07-15","cited_by_count":4,"area":null},{"id":"2111.00874","title":"An Uncertainty-Informed Framework for Trustworthy Fault Diagnosis in Safety-Critical Applications","created":"2021-10-08","cited_by_count":4,"area":null},{"id":"2111.09808","title":"Exploring the Limits of Epistemic Uncertainty Quantification in Low-Shot Settings","created":"2021-11-18","cited_by_count":4,"area":null},{"id":"2302.08406","title":"Entity Aware Modelling: A Survey","created":"2023-02-16","cited_by_count":4,"area":null},{"id":"2308.06964","title":"How inter-rater variability relates to aleatoric and epistemic uncertainty: a case study with deep learning-based paraspinal muscle segmentation","created":"2023-08-14","cited_by_count":4,"area":null},{"id":"2408.12175","title":"Measuring Orthogonality as the Blind-Spot of Uncertainty Disentanglement","created":"2024-08-22","cited_by_count":4,"area":null},{"id":"2210.03649","title":"How to Enable Uncertainty Estimation in Proximal Policy Optimization","created":"2022-10-07","cited_by_count":3,"area":null},{"id":"2211.06233","title":"Comparison of Uncertainty Quantification with Deep Learning in Time Series Regression","created":"2022-11-11","cited_by_count":3,"area":null},{"id":"2403.09228","title":"Uncertainty Quantification for cross-subject Motor Imagery classification","created":"2024-03-14","cited_by_count":3,"area":null},{"id":"2403.17212","title":"Sanity Checks for Explanation Uncertainty","created":"2024-03-25","cited_by_count":3,"area":null},{"id":"2406.18787","title":"Unified Uncertainties: Combining Input, Data and Model Uncertainty into a Single Formulation","created":"2024-06-26","cited_by_count":3,"area":null},{"id":"2501.11258","title":"Enhancing Uncertainty Estimation in Semantic Segmentation via Monte-Carlo Frequency Dropout","created":"2025-01-20","cited_by_count":3,"area":null},{"id":"2104.01865","title":"An Artificial Intelligence Framework for Bidding Optimization with Uncertainty in Multiple Frequency Reserve Markets","created":"2021-04-05","cited_by_count":2,"area":null},{"id":"2210.16938","title":"A view on model misspecification in uncertainty quantification","created":"2022-10-30","cited_by_count":2,"area":null},{"id":"2405.05286","title":"Tiny Deep Ensemble: Uncertainty Estimation in Edge AI Accelerators via Ensembling Normalization Layers with Shared Weights","created":"2024-05-07","cited_by_count":2,"area":null},{"id":"2504.06915","title":"An Analysis of Temporal Dropout in Earth Observation Time Series for Regression Tasks","created":"2025-04-09","cited_by_count":2,"area":null},{"id":"2507.00082","title":"Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission","created":"2025-06-30","cited_by_count":2,"area":null},{"id":"2507.04814","title":"UDF-GMA: Uncertainty Disentanglement and Fusion for General Movement Assessment","created":"2025-07-07","cited_by_count":2,"area":null},{"id":"2507.12913","title":"Robust Explanations Through Uncertainty Decomposition: A Path to Trustworthier AI","created":"2025-07-17","cited_by_count":2,"area":null},{"id":"2512.23753","title":"Generalized Regularized Evidential Deep Learning Models: Theory and Comprehensive Evaluation","created":"2025-12-27","cited_by_count":2,"area":null},{"id":"2204.09502","title":"UNBUS: Uncertainty-aware Deep Botnet Detection System in Presence of Perturbed Samples","created":"2022-04-18","cited_by_count":1,"area":null},{"id":"2301.06002","title":"ACTIVE: A Deep Model for Sperm and Impurity Detection in Microscopic Videos","created":"2023-01-15","cited_by_count":1,"area":null},{"id":"2308.06129","title":"Uncertainty Quantification for Image-based Traffic Prediction across Cities","created":"2023-08-11","cited_by_count":1,"area":null},{"id":"2309.12095","title":"Bayesian sparsification for deep neural networks with Bayesian model reduction","created":"2023-09-21","cited_by_count":1,"area":null},{"id":"2310.03393","title":"Uncertainty quantification for deep learning-based schemes for solving high-dimensional backward stochastic differential equations","created":"2023-10-05","cited_by_count":1,"area":null},{"id":"2312.15686","title":"PULASki: Learning inter-rater variability using statistical distances to improve probabilistic segmentation","created":"2023-12-25","cited_by_count":1,"area":null},{"id":"2407.04726","title":"Data-Driven Prediction and Uncertainty Quantification of PWR Crud-Induced Power Shift Using Convolutional Neural Networks","created":"2024-06-27","cited_by_count":1,"area":null},{"id":"2507.01032","title":"An Uncertainty-Aware Dynamic Decision Framework for Progressive Multi-Omics Integration in Classification Tasks","created":"2025-06-20","cited_by_count":1,"area":null},{"id":"2511.21223","title":"Maxitive Donsker-Varadhan Formulation for Possibilistic Variational Inference","created":"2025-11-26","cited_by_count":1,"area":null},{"id":"2602.22747","title":"Set-based v.s. Distribution-based Representations of Epistemic Uncertainty: A Comparative Study","created":"2026-02-26","cited_by_count":1,"area":null},{"id":"2603.22988","title":"Robustness Quantification and Uncertainty Quantification: Comparing Two Methods for Assessing the Reliability of Classifier Predictions","created":"2026-03-24","cited_by_count":1,"area":null},{"id":"2606.03471","title":"A formal definition and meta-model for a machine theory of mind","created":"2026-06-02","cited_by_count":1,"area":null},{"id":"2108.08712","title":"Teaching Uncertainty Quantification in Machine Learning through Use Cases","created":"2021-08-19","cited_by_count":0,"area":null},{"id":"2110.06435","title":"Dropout Prediction Uncertainty Estimation Using Neuron Activation Strength","created":"2021-10-13","cited_by_count":0,"area":null},{"id":"2201.08418","title":"SoftDropConnect (SDC) -- Effective and Efficient Quantification of the Network Uncertainty in Deep MR Image Analysis","created":"2022-01-20","cited_by_count":0,"area":null},{"id":"2207.09031","title":"Decorrelative Network Architecture for Robust Electrocardiogram Classification","created":"2022-07-19","cited_by_count":0,"area":null},{"id":"2211.06250","title":"Disentangled Uncertainty and Out of Distribution Detection in Medical Generative Models","created":"2022-11-11","cited_by_count":0,"area":null},{"id":"2305.19265","title":"Probabilistic computation and uncertainty quantification with emerging covariance","created":"2023-05-30","cited_by_count":0,"area":null},{"id":"2310.06105","title":"Quantifying Uncertainty in Deep Learning Classification with Noise in Discrete Inputs for Risk-Based Decision Making","created":"2023-10-09","cited_by_count":0,"area":null},{"id":"2401.06195","title":"NeuSpin: Design of a Reliable Edge Neuromorphic System Based on Spintronics for Green AI","created":"2024-01-11","cited_by_count":0,"area":null},{"id":"2407.03241","title":"Terrain Classification Enhanced with Uncertainty for Space Exploration Robots from Proprioceptive Data","created":"2024-07-03","cited_by_count":0,"area":null},{"id":"2407.12609","title":"Instance-wise Uncertainty for Class Imbalance in Semantic Segmentation","created":"2024-07-17","cited_by_count":0,"area":null},{"id":"2407.12626","title":"Domain-specific or Uncertainty-aware models: Does it really make a difference for biomedical text classification?","created":"2024-07-17","cited_by_count":0,"area":null},{"id":"2410.07725","title":"Towards Trustworthy Web Attack Detection: An Uncertainty-Aware Ensemble Deep Kernel Learning Model","created":"2024-10-10","cited_by_count":0,"area":null},{"id":"2411.15944","title":"Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout","created":"2024-11-24","cited_by_count":0,"area":null},{"id":"2412.10679","title":"U-FaceBP: Uncertainty-aware Bayesian Ensemble Deep Learning for Face Video-based Blood Pressure Estimation","created":"2024-12-14","cited_by_count":0,"area":null},{"id":"2506.17958","title":"ELMAR: Enhancing LiDAR Detection with 4D Radar Motion Awareness and Cross-modal Uncertainty","created":"2025-06-22","cited_by_count":0,"area":null},{"id":"2508.11961","title":"PEdger++: Practical Edge Detection via Assembling Cross Information","created":"2025-08-16","cited_by_count":0,"area":null},{"id":"2602.17028","title":"Forecasting Anomaly Precursors via Uncertainty-Aware Time-Series Ensembles","created":"2026-02-19","cited_by_count":0,"area":null},{"id":"2602.19498","title":"Softmax is not Enough (for Adaptive Conformal Classification)","created":"2026-02-23","cited_by_count":0,"area":null},{"id":"2603.24524","title":"No Single Metric Tells the Whole Story: A Multi-Dimensional Evaluation Framework for Uncertainty Attributions","created":"2026-03-25","cited_by_count":0,"area":null},{"id":"2604.04153","title":"Uncertainty-Aware Test-Time Adaptation for Cross-Region Spatio-Temporal Fusion of Land Surface Temperature","created":"2026-04-05","cited_by_count":0,"area":null},{"id":"2605.00600","title":"Possibilistic Predictive Uncertainty for Deep Learning","created":"2026-05-01","cited_by_count":0,"area":null},{"id":"2605.22390","title":"A Posterior-Predictive Variance Decomposition for Epistemic and Aleatoric Uncertainty in Wind Power Forecasting","created":"2026-05-21","cited_by_count":0,"area":null},{"id":"2605.26569","title":"Distribution-Aware Conformal Prediction: A Framework for generating efficient prediction intervals for time series","created":"2026-05-26","cited_by_count":0,"area":null},{"id":"2606.10777","title":"Can we trust our models? Epistemic calibration in second-order classification","created":"2026-06-09","cited_by_count":0,"area":null},{"id":"2607.11412","title":"Uncertainty Quantification for EO Regression Tasks: Building Height, Tree Canopy Height and Above-ground Biomass Estimation","created":"2026-07-13","cited_by_count":0,"area":null},{"id":"2607.16378","title":"Disentangling Model and Human Data Uncertainty in Apparent Facial Age Estimation","created":"2026-07-17","cited_by_count":0,"area":null},{"id":"2607.28248","title":"Uncertainty quantification for trustworthy deep learning: Methods and measures","created":"2026-07-30","cited_by_count":0,"area":null},{"id":"2608.14768","title":"Uncertainty Identifies Difficult Samples Across Methods: A Multi-Task Study on a Heterogeneous Skin Lesion Dataset","created":"2026-08-14","cited_by_count":0,"area":null},{"id":"2609.11366","title":"Local Robustness Quantification for Naive Bayes Classifiers and Generative Forests: a General Approach","created":"2026-09-10","cited_by_count":0,"area":null}],"next_cursor":null}