Uncertainty Quantification in Machine Learning for Engineering Design
and Health Prognostics: A Tutorial

Uncertainty Quantification in Machine Learning for Engineering Design and Health Prognostics: A Tutorial

7 May 2023

Olga Fink

Papers citing "Uncertainty Quantification in Machine Learning for Engineering Design and Health Prognostics: A Tutorial"

19 / 19 papers shown

Title
Improving Medical Diagnostics with Vision-Language Models: Convex Hull-Based Uncertainty Analysis Ferhat Ozgur Catak Murat Kuzlu Taylor Patrick 81 0 0 24 Nov 2024
Expert-elicitation method for non-parametric joint priors using normalizing flows F. Bockting Stefan T. Radev Paul-Christian Burkner BDL 88 1 0 24 Nov 2024
Legitimate ground-truth-free metrics for deep uncertainty classification scoring Arthur Pignet Chiara Regniez John Klein 52 1 0 30 Oct 2024
Uncertainty Quantification in Large Language Models Through Convex Hull Analysis Ferhat Ozgur Catak Murat Kuzlu UQCV 36 4 0 28 Jun 2024
Towards a Probabilistic Fusion Approach for Robust Battery Prognostics Jokin Alcibar J. Aizpurua E. Zugasti 25 1 0 24 May 2024
Towards Out-of-Distribution Detection for breast cancer classification in Point-of-Care Ultrasound Imaging Jennie Karlsson Marisa Wodrich Niels Christian Overgaard Freja Sahlin Kristina Laang Anders Heyden Ida Arvidsson 16 0 0 29 Feb 2024
A Priori Uncertainty Quantification of Reacting Turbulence Closure Models using Bayesian Neural Networks Graham Pash M. Hassanaly S. Yellapantula AI4CE 24 0 0 28 Feb 2024
Probabilistic Neural Networks (PNNs) for Modeling Aleatoric Uncertainty in Scientific Machine Learning Farhad Pourkamali-Anaraki Jamal F. Husseini Scott E. Stapleton UD 25 2 0 21 Feb 2024
Uncertainty Quantification on Clinical Trial Outcome Prediction Tianyi Chen Yingzhou Lu Nan Hao Capucine Van Rechem Jintai Chen Tianfan Fu 11 21 0 07 Jan 2024
A comparison of machine learning surrogate models of street-scale flooding in Norfolk, Virginia Diana McSpadden S. Goldenberg Bina Roy M. Schram J. Goodall H. Lipford AI4CE 12 3 0 26 Jul 2023
Perturbation-Assisted Sample Synthesis: A Novel Approach for Uncertainty Quantification Yifei Liu Rex Shen Xiaotong Shen DiffM 16 1 0 30 May 2023
Machine learning pipeline for battery state of health estimation D. Roman Saurabh Saxena Valentin Robu Michael G. Pecht David Flynn 18 374 0 01 Feb 2021
An adaptive artificial neural network-based generative design method for layout designs Chaojun Qian Renkai Tan W. Ye AI4CE 10 26 0 29 Jan 2021
Projected Stein Variational Gradient Descent Peng Chen Omar Ghattas BDL 50 68 0 09 Feb 2020
Deep Reinforcement Learning for Autonomous Driving: A Survey B. R. Kiran Ibrahim Sobh V. Talpaert Patrick Mannion A. A. Sallab S. Yogamani P. Pérez 143 1,599 0 02 Feb 2020
A Stein variational Newton method Gianluca Detommaso Tiangang Cui Alessio Spantini Youssef Marzouk Robert Scheichl 53 114 0 08 Jun 2018
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 268 5,635 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,042 0 06 Jun 2015
Recursive co-kriging model for Design of Computer experiments with multiple levels of fidelity with an application to hydrodynamic Loic Le Gratiet AI4CE 86 290 0 02 Oct 2012