{"total":36,"rows":[{"id":"2107.03342","title":"A Survey of Uncertainty in Deep Neural Networks","created":"2021-07-07","cited_by_count":680,"area":null},{"id":"2308.01222","title":"Calibration in Deep Learning: A Survey of the State-of-the-Art","created":"2023-08-02","cited_by_count":75,"area":null},{"id":"2104.05788","title":"Spatially Varying Label Smoothing: Capturing Uncertainty from Expert Annotations","created":"2021-04-12","cited_by_count":31,"area":null},{"id":"2209.07601","title":"Towards Improving Calibration in Object Detection Under Domain Shift","created":"2022-09-15","cited_by_count":26,"area":null},{"id":"2207.06873","title":"BayesCap: Bayesian Identity Cap for Calibrated Uncertainty in Frozen Neural Networks","created":"2022-07-14","cited_by_count":23,"area":null},{"id":"2109.05263","title":"Class-Distribution-Aware Calibration for Long-Tailed Visual Recognition","created":"2021-09-11","cited_by_count":19,"area":null},{"id":"2104.12376","title":"Recalibration of Aleatoric and Epistemic Regression Uncertainty in Medical Imaging","created":"2021-04-26","cited_by_count":18,"area":null},{"id":"2402.05355","title":"A Survey on Safe Multi-Modal Learning System","created":"2024-02-08","cited_by_count":15,"area":null},{"id":"2311.03570","title":"Cal-DETR: Calibrated Detection Transformer","created":"2023-11-06","cited_by_count":11,"area":null},{"id":"2206.07795","title":"On Calibrated Model Uncertainty in Deep Learning","created":"2022-06-15","cited_by_count":7,"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":"2502.05964","title":"Revisiting Gradient-based Uncertainty for Monocular Depth Estimation","created":"2025-02-09","cited_by_count":6,"area":null},{"id":"2306.08981","title":"Overcoming the Limitations of Localization Uncertainty: Efficient & Exact Non-Linear Post-Processing and Calibration","created":"2023-06-15","cited_by_count":5,"area":null},{"id":"2504.18346","title":"Comparing Uncertainty Measurement and Mitigation Methods for Large Language Models: A Systematic Review","created":"2025-04-25","cited_by_count":4,"area":null},{"id":"2106.07533","title":"Posterior Temperature Optimization in Variational Inference for Inverse Problems","created":"2021-06-11","cited_by_count":3,"area":null},{"id":"2406.02411","title":"Decoupling of neural network calibration measures","created":"2024-06-04","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":"2302.05137","title":"Realistic Conversational Question Answering with Answer Selection based on Calibrated Confidence and Uncertainty Measurement","created":"2023-02-10","cited_by_count":2,"area":null},{"id":"2405.18351","title":"Evaluating Bayesian deep learning for radio galaxy classification","created":"2024-05-28","cited_by_count":2,"area":null},{"id":"2505.22803","title":"CLUE: Neural Networks Calibration via Learning Uncertainty-Error alignment","created":"2025-05-28","cited_by_count":2,"area":null},{"id":"2506.17968","title":"h-calibration: Rethinking Classifier Recalibration with Probabilistic Error-Bounded Objective","created":"2025-06-22","cited_by_count":2,"area":null},{"id":"2107.00191","title":"Unsupervised Model Drift Estimation with Batch Normalization Statistics for Dataset Shift Detection and Model Selection","created":"2021-07-01","cited_by_count":1,"area":null},{"id":"2111.10480","title":"TransMorph: Transformer for unsupervised medical image registration","created":"2021-11-19","cited_by_count":1,"area":null},{"id":"2303.15057","title":"Towards Unbiased Calibration using Meta-Regularization","created":"2023-03-27","cited_by_count":1,"area":null},{"id":"2307.02736","title":"An Uncertainty Aided Framework for Learning based Liver $T_1\\rho$ Mapping and Analysis","created":"2023-07-06","cited_by_count":1,"area":null},{"id":"2309.13866","title":"On Calibration of Modern Quantized Efficient Neural Networks","created":"2023-09-25","cited_by_count":1,"area":null},{"id":"2409.03470","title":"Improving Uncertainty-Error Correspondence in Deep Bayesian Medical Image Segmentation","created":"2024-09-05","cited_by_count":1,"area":null},{"id":"2410.18108","title":"A Deep Learning Approach to Estimate Canopy Height and Uncertainty by Integrating Seasonal Optical, SAR and Limited GEDI LiDAR Data over Northern Forests","created":"2024-10-08","cited_by_count":1,"area":null},{"id":"2602.12975","title":"Extending confidence calibration to generalised measures of variation","created":"2026-02-13","cited_by_count":1,"area":null},{"id":"2301.13444","title":"Rethinking Soft Label in Label Distribution Learning Perspective","created":"2023-01-31","cited_by_count":0,"area":null},{"id":"2401.03664","title":"Dual-Channel Reliable Breast Ultrasound Image Classification Based on Explainable Attribution and Uncertainty Quantification","created":"2024-01-08","cited_by_count":0,"area":null},{"id":"2504.13465","title":"Are you SURE? Enhancing Multimodal Pretraining with Missing Modalities through Uncertainty Estimation","created":"2025-04-18","cited_by_count":0,"area":null},{"id":"2504.14050","title":"MMformer with Adaptive Transferable Attention: Advancing Multivariate Time Series Forecasting for Environmental Applications","created":"2025-04-18","cited_by_count":0,"area":null},{"id":"2509.19563","title":"Uncertainty in Semantic Language Modeling with PIXELS","created":"2025-09-23","cited_by_count":0,"area":null},{"id":"2602.11973","title":"Confidence-Uncertainty Boundary Calibration for Bayesian Deep Learning in Medical Image Analysis","created":"2026-02-12","cited_by_count":0,"area":null},{"id":"2605.16570","title":"A Cubing Strategy for Identifying Stable Hyperparameter Regions for Uncertainty Quantification in Spatial Deep Learning","created":"2026-05-15","cited_by_count":0,"area":null}],"next_cursor":null}