A review of uncertainty quantification in deep learning: Techniques, applications and challenges

Uncertainty quantification for data-driven turbulence modelling with mondrian forests

(2021) Ashley Scillitoe et al.   JOURNAL OF COMPUTATIONAL PHYSICS

A deep learning just-in-time modeling approach for soft sensor based on variational autoencoder

(2020) Fan Guo et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

Blind Spot Detection for Safe Sim-to-Real Transfer

(2020) Ramya Ramakrishnan et al.   JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH

Deep Learning Uncertainty and Confidence Calibration for the Five-class Polyp Classification from Colonoscopy

(2020) Gustavo Carneiro et al.   MEDICAL IMAGE ANALYSIS

Demystifying Brain Tumor Segmentation Networks: Interpretability and Uncertainty Analysis

(2020) Parth Natekar et al.   Frontiers in Computational Neuroscience

Recent advances in deep learning

(2020) Xizhao Wang et al.   International Journal of Machine Learning and Cybernetics

Bayesian neural networks for flight trajectory prediction and safety assessment

(2020) Xiaoge Zhang et al.   DECISION SUPPORT SYSTEMS

An improved deep network for tissue microstructure estimation with uncertainty quantification

(2020) Chuyang Ye et al.   MEDICAL IMAGE ANALYSIS

Automated Detection of Presymptomatic Conditions in Spinocerebellar Ataxia Type 2 Using Monte Carlo Dropout and Deep Neural Network Techniques with Electrooculogram Signals

(2020) Catalin Stoean et al.   SENSORS

Critical Temperature Prediction for a Superconductor: A Variational Bayesian Neural Network Approach

(2020) Thanh Dung Le et al.   IEEE TRANSACTIONS ON APPLIED SUPERCONDUCTIVITY

DR|GRADUATE: Uncertainty-aware deep learning-based diabetic retinopathy grading in eye fundus images

(2020) Teresa Araújo et al.   MEDICAL IMAGE ANALYSIS

Uncertainty-aware domain alignment for anatomical structure segmentation

(2020) Cheng Bian et al.   MEDICAL IMAGE ANALYSIS

Ranking Information Extracted from Uncertainty Quantification of the Prediction of a Deep Learning Model on Medical Time Series Data

(2020) Ruxandra Stoean et al.   Mathematics

Personalizing Activity Recognition Models Through Quantifying Different Types of Uncertainty Using Wearable Sensors

(2020) Ali Akbari et al.   IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING

Uncertainty-aware multi-view co-training for semi-supervised medical image segmentation and domain adaptation

(2020) Yingda Xia et al.   MEDICAL IMAGE ANALYSIS

Integrating uncertainty in deep neural networks for MRI based stroke analysis

(2020) Lisa Herzog et al.   MEDICAL IMAGE ANALYSIS

Calibration of deep probabilistic models with decoupled bayesian neural networks

(2020) Juan Maroñas et al.   NEUROCOMPUTING

Probabilistic inference of Bayesian neural networks with generalized expectation propagation

(2020) Jing Zhao et al.   NEUROCOMPUTING

Confidence Calibration and Predictive Uncertainty Estimation for Deep Medical Image Segmentation

(2020) Alireza Mehrtash et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Information Aware max-norm Dirichlet networks for predictive uncertainty estimation

(2020) Theodoros Tsiligkaridis   NEURAL NETWORKS

A Bayesian Deep Learning Framework for End-To-End Prediction of Emotion From Heartbeat

(2020) Ross Harper et al.   IEEE Transactions on Affective Computing

Scalable Bayesian Uncertainty Quantification in Imaging Inverse Problems via Convex Optimization

(2019) Audrey Repetti et al.   SIAM Journal on Imaging Sciences

Bayesian QuickNAT: Model uncertainty in deep whole-brain segmentation for structure-wise quality control

(2019) Abhijit Guha Roy et al.   NEUROIMAGE

Bayesian Recurrent Neural Network Models for Forecasting and Quantifying Uncertainty in Spatial-Temporal Data

(2019) Patrick McDermott et al.   Entropy

Optimization under Uncertainty in the Era of Big Data and Deep Learning: When Machine Learning Meets Mathematical Programming

(2019) Chao Ning et al.   COMPUTERS & CHEMICAL ENGINEERING

The MBPEP: a deep ensemble pruning algorithm providing high quality uncertainty prediction

(2019) Ruihan Hu et al.   APPLIED INTELLIGENCE

Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data

(2019) Yinhao Zhu et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Quantifying model form uncertainty in Reynolds-averaged turbulence models with Bayesian deep neural networks

(2019) Nicholas Geneva et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Adversarial uncertainty quantification in physics-informed neural networks

(2019) Yibo Yang et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks

(2019) Guotai Wang et al.   NEUROCOMPUTING

Reliable deep-learning-based phase imaging with uncertainty quantification

(2019) Yujia Xue et al.   Optica

Distribution-free uncertainty quantification for kernel methods by gradient perturbations

(2019) Balázs Cs. Csáji et al.   MACHINE LEARNING

Improving predictive uncertainty estimation using Dropout–Hamiltonian Monte Carlo

(2019) Sergio Hernández et al.   SOFT COMPUTING

Bayesian deep learning based method for probabilistic forecast of day-ahead electricity prices

(2019) Alessandro Brusaferri et al.   APPLIED ENERGY

One-dimensional modeling of fractional flow reserve in coronary artery disease: Uncertainty quantification and Bayesian optimization

(2019) Minglang Yin et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Modeling and Planning Under Uncertainty Using Deep Neural Networks

(2019) Daniel L. Marino et al.   IEEE Transactions on Industrial Informatics

Hashing with Mutual Information

(2019) Fatih Cakir et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Robust Visual Tracking based on Variational Auto-encoding Markov Chain Monte Carlo

(2019) Junseok Kwon   INFORMATION SCIENCES

Exploring uncertainty measures in deep networks for Multiple Sclerosis lesion detection and segmentation

(2019) Tanya Nair et al.   MEDICAL IMAGE ANALYSIS

An improved fuzzy ARTMAP and Q-learning agent model for pattern classification

(2019) Farhad Pourpanah et al.   NEUROCOMPUTING

Accuracy, uncertainty, and adaptability of automatic myocardial ASL segmentation using deep CNN

(2019) Hung P. Do et al.   MAGNETIC RESONANCE IN MEDICINE

Accurate and robust deep learning-based segmentation of the prostate clinical target volume in ultrasound images

(2019) Davood Karimi et al.   MEDICAL IMAGE ANALYSIS

Galaxy Zoo: probabilistic morphology through Bayesian CNNs and active learning

(2019) Mike Walmsley et al.   MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY

ARA: accurate, reliable and active histopathological image classification framework with Bayesian deep learning

(2019) Łukasz Rączkowski et al.   Scientific Reports

Deep spectral learning for label-free optical imaging oximetry with uncertainty quantification

(2019) Rongrong Liu et al.   Light-Science & Applications

Probabilistic spatiotemporal wind speed forecasting based on a variational Bayesian deep learning model

(2019) Yongqi Liu et al.   APPLIED ENERGY

Uncertainty quantification using Bayesian neural networks in classification: Application to biomedical image segmentation

(2019) Yongchan Kwon et al.   COMPUTATIONAL STATISTICS & DATA ANALYSIS

Deep ensemble learning based probabilistic load forecasting in smart grids

(2019) Yandong Yang et al.   ENERGY

Exploiting Epistemic Uncertainty of Anatomy Segmentation for Anomaly Detection in Retinal OCT

(2019) Philipp Seebock et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Using Bayesian Deep Learning to Capture Uncertainty for Residential Net Load Forecasting

(2019) Mingyang Sun et al.   IEEE TRANSACTIONS ON POWER SYSTEMS

Targeting the uncertainty of predictions at patient-level using an ensemble of classifiers coupled with calibration methods, Venn-ABERS, and Conformal Predictors: A case study in AD

(2019) Telma Pereira et al.   JOURNAL OF BIOMEDICAL INFORMATICS

Commensal correlation network between segmentation and direct area estimation for bi-ventricle quantification

(2019) Gongning Luo et al.   MEDICAL IMAGE ANALYSIS

Uncertainty and interpretability in convolutional neural networks for semantic segmentation of colorectal polyps

(2019) Kristoffer Wickstrøm et al.   MEDICAL IMAGE ANALYSIS

An attention-based neural framework for uncertainty identification on social media texts

(2019) Xu Han et al.   TSINGHUA SCIENCE AND TECHNOLOGY

Automated Muscle Segmentation from Clinical CT Using Bayesian U-Net for Personalized Musculoskeletal Modeling

(2019) Yuta Hiasa et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

On Modelling Label Uncertainty in Deep Neural Networks: Automatic Estimation of Intra- Observer Variability in 2D Echocardiography Quality Assessment

(2019) Zhibin Liao et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Uncertainty-Aware Organ Classification for Surgical Data Science Applications in Laparoscopy

(2018) Sara Moccia et al.   IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING

Interactive Medical Image Segmentation Using Deep Learning With Image-Specific Fine Tuning

(2018) Guotai Wang et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Neural Network-Based Uncertainty Quantification: A Survey of Methodologies and Applications

(2018) H. M. Dipu Kabir et al.   IEEE Access

Deep echo state networks with uncertainty quantification for spatio-temporal forecasting

(2018) Patrick L. McDermott et al.   ENVIRONMETRICS

Rough extreme learning machine: A new classification method based on uncertainty measure

(2018) Lin Feng et al.   NEUROCOMPUTING

Crowdsourcing Thousands of Specialized Labels: A Bayesian Active Training Approach

(2017) Maximilien Servajean et al.   IEEE TRANSACTIONS ON MULTIMEDIA

Linear Maximum Margin Classifier for Learning from Uncertain Data

(2017) Christos Tzelepis et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

(2017) Vijay Badrinarayanan et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Fully Convolutional Networks for Semantic Segmentation

(2017) Evan Shelhamer et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Variational Inference: A Review for Statisticians

(2017) David M. Blei et al.   JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

Measures of uncertainty for neighborhood rough sets

(2017) Yumin Chen et al.   KNOWLEDGE-BASED SYSTEMS

A survey on deep learning in medical image analysis

(2017) Geert Litjens et al.   MEDICAL IMAGE ANALYSIS

Echo State Networks for data-driven downhole pressure estimation in gas-lift oil wells

(2017) Eric A. Antonelo et al.   NEURAL NETWORKS

Addressing uncertainty in atomistic machine learning

(2017) Andrew A. Peterson et al.   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

Active learning enabled activity recognition

(2017) H M Sajjad Hossain et al.   Pervasive and Mobile Computing

Leveraging uncertainty information from deep neural networks for disease detection

(2017) Christian Leibig et al.   Scientific Reports

Bayesian Recurrent Neural Network for Language Modeling

(2016) Jen-Tzung Chien et al.   IEEE Transactions on Neural Networks and Learning Systems

A study of active learning methods for named entity recognition in clinical text

(2015) Yukun Chen et al.   JOURNAL OF BIOMEDICAL INFORMATICS

Sentiment analysis: Bayesian Ensemble Learning

(2014) E. Fersini et al.   DECISION SUPPORT SYSTEMS

Uncertainty-Aware Guided Volume Segmentation

(2010) Jorg-Stefan Prassni et al.   IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS

An ensemble uncertainty aware measure for directed hill climbing ensemble pruning

(2010) Ioannis Partalas et al.   MACHINE LEARNING

Aleatory or epistemic? Does it matter?

(2008) Armen Der Kiureghian et al.   STRUCTURAL SAFETY