Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methods

Cited by (1,004)

Items 501–600 of 1,004

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2. On Measures of Uncertainty in Classification
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3. Going Beyond One-Hot Encoding in Classification: Can Human Uncertainty Improve Model Performance in Earth Observation?
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4. Analysis of data‐driven models for predicting fatigue strength of steel components with uncertainty quantification
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5. Uncertainty Nonlinearly Guided Learning Framework for Full-Wave Inverse Scattering
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6. Heat Equation Stein Variational Ensemble: Rethinking and Advancing Uncertainty-Aware Soft Sensor Modeling
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7. Uncertainty-based knowledge distillation for Bayesian deep neural network compression
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8. Swarm optimization based heterogeneous machine learning techniques for enhanced landslide susceptibility assessment with comprehensive uncertainty quantification
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9. Quantum-Cognitive Neural Networks: Assessing Confidence and Uncertainty with Human Decision-Making Simulations
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10. CreINNs: Credal-Set Interval Neural Networks for Uncertainty Estimation in Classification Tasks
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11. Enhancing uncertainty quantification in drug discovery with censored regression labels
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12. Recurrent Reinforcement Learning Strategy with a Parameterized Agent for Online Scheduling of a State Task Network Under Uncertainty
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13. Empirical validation of size effects in sub-sized tensile specimens for nuclear structural materials
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14. Uncertainty Quantification in AI-Based Measurement Systems
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15. Uncertainty quantification of wind gust predictions in the northeast United States: An evidential neural network and explainable artificial intelligence approach
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16. Beyond accuracy: a framework for evaluating algorithmic bias and performance, applied to automated sleep scoring
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17. Bridging Traditional-Statistics and Machine-Learning Approaches in Psychology: Navigating Small Samples, Measurement Error, Nonindependent Observations, and Missing Data
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18. The Enemies of Reliable and Useful Clinical Prediction Models: A Review of Statistical and Scientific Challenges
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19. Interplay between Bayesian neural networks and deep learning: A survey
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20. Upgrading Reliability in Molecular Property Prediction by Robust Quantification of Uncertainty from Machine Learning Models
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21. Benchmarking Scalable Predictive Uncertainty in Text Classification
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22. Data analytics for improved closest hospital suggestion for EMS operations in New York City
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23. Using Bayesian Deep Learning to Infer Planet Mass from Gaps in Protoplanetary Disks
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24. Simple Optimal Sampling Algorithm to Strengthen Digital Soil Mapping Using the Spatial Distribution of Machine Learning Predictive Uncertainty: A Case Study for Field Capacity Prediction
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25. Adaptive Sampling of Latent Phenomena using Heterogeneous Robot Teams (ASLaP-HR)
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26. An agent-based simulator for quantifying the cost of uncertainty in production systems
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27. Compound Density Networks for Risk Prediction using Electronic Health Records
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28. Investigations on machine learning-based control-oriented modeling using historical thermal data of buildings
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29. An active learning framework and assessment of inter-annotator agreement facilitate automated recogniser development for vocalisations of a rare species, the southern black-throated finch (Poephila cincta cincta)
    John M. van Osta, Brad Dreis, Edward A. Meyer, Laura F. Grogan, James Guy Castley · 2023 · Ecological Informatics
30. Uncertainty Calibrations of Deep-Learning Schemes for Full-Wave Inverse Scattering Problems
    Siyuan He, Gensheng Zhang, Zhun Wei · 2023 · IEEE Transactions on Geoscience and Remote Sensing
31. Neural-physics multi-fidelity model with active learning and uncertainty quantification for GPU-enabled microfluidic concentration gradient generator design
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32. Uncertainty Analysis of Deep Kernel Learning Methods on Diabetic Retinopathy Grading
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33. Sample-efficient estimation of entanglement entropy through supervised learning
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34. Mitigating Label Noise through Data Ambiguation
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35. Formal Verification of Unknown Dynamical Systems via Gaussian Process Regression
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36. Variational Neural Networks
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37. Are all outliers alike? On Understanding the Diversity of Outliers for Detecting OODs
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38. Calibration-Aware Bayesian Learning
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39. Uncertainty-Boosted Robust Video Activity Anticipation
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40. Measurement and Applications: Artificial Intelligence in the Field of Measurement Applications
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42. Reliability-improved machine learning model using knowledge-embedded learning approach for smart manufacturing
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43. Uncertainty-Aware Reinforcement Learning for Portfolio Optimization
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44. Wind speed vertical extrapolation model validation under uncertainty
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45. A temporal stochastic bias correction using a machine learning attention model
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46. Uncertain Numbers
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47. Predicting Stress–Strain Curve with Confidence: Balance Between Data Minimization and Uncertainty Quantification by a Dual Bayesian Model
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48. Prediction and Uncertainty Quantification of the Fatigue Life of Corroded Cable Steel Wires Using a Bayesian Physics-Informed Neural Network
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49. On the ethical and moral dimensions of using artificial intelligence for evidence synthesis
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50. An Optimized 1-D CNN-LSTM Approach for Fault Diagnosis of Rolling Bearings Considering Epistemic Uncertainty
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51. Recursive Annotation for Negative Labeling in Data-Driven Mineral Prospectivity Mapping
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52. Financial Time Series Uncertainty: A Review of Probabilistic AI Applications
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53. Improving monte carlo dropout uncertainty estimation with stable output layers
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54. Bayesian continual learning and forgetting in neural networks
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55. An integrated framework for reliability analysis and design optimization using input, simulation, and experimental data: Confidence-based design optimization under aleatory and epistemic uncertainty
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56. Combining Bayesian and Evidential Uncertainty Quantification for Improved Bioactivity Modeling
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57. Hybrid modelling approaches in process intensification: A thorough review
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58. Predictable artificial intelligence
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59. Active Object Detection with Epistemic Uncertainty and Hierarchical Information Aggregation
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60. Scarce Data in Intelligent Technical Systems: Causes, Characteristics, and Implications
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61. A Comparison of Uncertainty Quantification Methods for Active Learning in Image Classification
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62. RETRACTED ARTICLE: Robust adversarial uncertainty quantification for deep learning fine-tuning
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64. Harnessing uncertainty in radiotherapy auto-segmentation quality assurance
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66. Addressing Uncertainty on Machine Learning Models for Long-Period Fiber Grating Signal Conditioning Using Monte Carlo Method
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67. Heteroscedastic Gaussian processes for data normalisation in probabilistic novelty detection of a wind turbine
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68. From Hume to Wuhan: An Epistemological Journey on the Problem of Induction in COVID-19 Machine Learning Models and its Impact Upon Medical Research
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69. Uncertainty-aware self-supervised neural network for liver T 1 ρ mapping with relaxation constraint
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70. Incorporating algorithmic uncertainty into a clinical machine deep learning algorithm for urgent head CTs
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72. Confidence Aware Neural Networks for Skin Cancer Detection
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73. Leveraging control priors in deep reinforcement learning for robotics
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74. Generative Deep Learning Techniques for Traffic Matrix Estimation From Link Load Measurements
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75. On the Calibration of Uncertainty Estimation in LiDAR-Based Semantic Segmentation
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