Uncertainty Propagation in Deep Neural Networks Using Extended Kalman Filtering
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Abstract (arXiv)
Extended Kalman Filtering (EKF) can be used to propagate and quantify input uncertainty through a Deep Neural Network (DNN) assuming mild hypotheses on the input distribution. This methodology yields results comparable to existing methods of uncertainty propagation for DNNs while lowering the computational overhead considerably. Additionally, EKF allows model error to be naturally incorporated into the output uncertainty.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Sep 2018.
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Citing papers per year: 2021: 1; 2022: 2; 2023: 2; 2024: 0; 2025: 1; 2026: 2.
8 papers.
- 2023Propagation and Attribution of Uncertainty in Medical Imaging Pipelinescited by 5
- 2022A Trustworthy Framework for Medical Image Analysis with Deep Learningcited by 1
- 2025Assumed Density Filtering and Smoothing with Neural Network Surrogate Modelscited by 1
- 2021Performance Bounds for Neural Network Estimators: Applications in Fault Detectioncited by 0
- 2022Towards Trustworthy Healthcare AI: Attention-Based Feature Learning for COVID-19 Screening With Chest Radiographycited by 0
- 2023Uncertainty Propagation through Trained Deep Neural Networks Using Factor Graphscited by 0
- 2026Uncertainty propagation through trained multi-layer perceptrons: Exact analytical resultscited by 0
- 2026Uncertainty propagation in auto-regressive random neural network modelscited by 0
- 2026Uncertainty propagation in auto-regressive random neural network models20 Aug 2026
- 2026Uncertainty propagation through trained multi-layer perceptrons: Exact analytical results23 Jan 2026
- 2025Assumed Density Filtering and Smoothing with Neural Network Surrogate Models12 Nov 2025
- 2023Uncertainty Propagation through Trained Deep Neural Networks Using Factor Graphs10 Dec 2023
- 2023Propagation and Attribution of Uncertainty in Medical Imaging Pipelines28 Sep 2023
- 2022A Trustworthy Framework for Medical Image Analysis with Deep Learning6 Dec 2022
- 2022Towards Trustworthy Healthcare AI: Attention-Based Feature Learning for COVID-19 Screening With Chest Radiography19 Jul 2022
- 2021Performance Bounds for Neural Network Estimators: Applications in Fault Detection22 Mar 2021