Uncertainty Toolbox: an Open-Source Library for Assessing, Visualizing,
and Improving Uncertainty Quantification

Uncertainty Toolbox: an Open-Source Library for Assessing, Visualizing, and Improving Uncertainty Quantification

21 September 2021

Youngseog Chung

Papers citing "Uncertainty Toolbox: an Open-Source Library for Assessing, Visualizing, and Improving Uncertainty Quantification"

15 / 15 papers shown

Title
Lightning UQ Box: A Comprehensive Framework for Uncertainty Quantification in Deep Learning Nils Lehmann Jakob Gawlikowski Adam J. Stewart Vytautas Jancauskas Stefan Depeweg Eric T. Nalisnick N. Gottschling 42 0 0 04 Oct 2024
A novel fusion of Sentinel-1 and Sentinel-2 with climate data for crop phenology estimation using Machine Learning Shahab Aldin Shojaeezadeh Abdelrazek Elnashar Tobias Karl David Weber 40 0 0 16 Aug 2024
Full Shot Predictions for the DIII-D Tokamak via Deep Recurrent Networks I. Char Youngseog Chung J. Abbate E. Kolemen Jeff Schneider 43 4 0 18 Apr 2024
Uncertainty Quantification for Image-based Traffic Prediction across Cities Alexander Timans Nina Wiedemann Nishant Kumar Ye Hong Martin Raubal 18 1 0 11 Aug 2023
Distance Preserving Machine Learning for Uncertainty Aware Accelerator Capacitance Predictions S. Goldenberg M. Schram Kishansingh Rajput T. Britton C. Pappas Dawei Lu Jared Walden M. Radaideh Sarah Cousineau S. Harave 29 1 0 05 Jul 2023
Bayesian Optimization of Catalysis With In-Context Learning M. C. Ramos Shane S. Michtavy Marc D. Porosoff Andrew D. White BDL 44 30 0 11 Apr 2023
On the role of Model Uncertainties in Bayesian Optimization Jonathan Foldager Mikkel Jordahn Lars Kai Hansen Michael Riis Andersen 19 4 0 14 Jan 2023
Scalable Bayesian Uncertainty Quantification for Neural Network Potentials: Promise and Pitfalls Stephan Thaler Gregor Doehner J. Zavadlav 32 21 0 15 Dec 2022
Generalizing Bayesian Optimization with Decision-theoretic Entropies W. Neiswanger Lantao Yu Shengjia Zhao Chenlin Meng Stefano Ermon UQCV 43 11 0 04 Oct 2022
NeuralUQ: A comprehensive library for uncertainty quantification in neural differential equations and operators Zongren Zou Xuhui Meng Apostolos F. Psaros George Karniadakis AI4CE 25 36 0 25 Aug 2022
Transformer Neural Processes: Uncertainty-Aware Meta Learning Via Sequence Modeling Tung Nguyen Aditya Grover BDL UQCV 19 99 0 09 Jul 2022
Uncertainty Quantification for Deep Unrolling-Based Computational Imaging Canberk Ekmekci Müjdat Çetin UQCV 19 11 0 02 Jul 2022
Modular Conformal Calibration Charles Marx Shengjia Zhao W. Neiswanger Stefano Ermon 32 15 0 23 Jun 2022
A framework for benchmarking uncertainty in deep regression F. Schmähling Jörg Martin Clemens Elster UQCV 32 8 0 10 Sep 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,660 0 05 Dec 2016