Wolfgang Nowak
Orcid: 0000-0003-2583-8865Affiliations:
- University of Stuttgart, Germany
According to our database1,
Wolfgang Nowak
authored at least 23 papers
between 2011 and 2023.
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Bibliography
2023
Appl. Artif. Intell., December, 2023
The deep arbitrary polynomial chaos neural network or how Deep Artificial Neural Networks could benefit from data-driven homogeneous chaos theory.
Neural Networks, September, 2023
A fully Bayesian sparse polynomial chaos expansion approach with joint priors on the coefficients and global selection of terms.
J. Comput. Phys., September, 2023
IEEE Trans. Mob. Comput., March, 2023
2022
Replication Data for: Learning Groundwater Contaminant Diffusion-Sorption Processes with a Finite Volume Neural Network.
Dataset, November, 2022
Combining Crop Modeling with Remote Sensing Data Using a Particle Filtering Technique to Produce Real-Time Forecasts of Winter Wheat Yields under Uncertain Boundary Conditions.
Remote. Sens., 2022
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2022, 2022
2021
Sequential Design of Computer Experiments for the Computation of Bayesian Model Evidence.
SIAM/ASA J. Uncertain. Quantification, 2021
2020
Reliab. Eng. Syst. Saf., 2020
Exploratory-Phase-Free Estimation of GP Hyperparameters in Sequential Design Methods - At the Example of Bayesian Inverse Problems.
Frontiers Artif. Intell., 2020
Bayesian3 Active Learning for the Gaussian Process Emulator Using Information Theory.
Entropy, 2020
2019
The Connection between Bayesian Inference and Information Theory for Model Selection, Information Gain and Experimental Design.
Entropy, 2019
2018
Incomplete statistical information limits the utility of high-order polynomial chaos expansions.
Reliab. Eng. Syst. Saf., 2018
Comparison of data-driven uncertainty quantification methods for a carbon dioxide storage benchmark scenario.
CoRR, 2018
2017
Sequential Design of Computer Experiments for the Solution of Bayesian Inverse Problems.
SIAM/ASA J. Uncertain. Quantification, 2017
The rocky road to extended simulation frameworks covering uncertainty, inversion, optimization and control.
Environ. Model. Softw., 2017
2016
Entropy-Based Experimental Design for Optimal Model Discrimination in the Geosciences.
Entropy, 2016
2013
Towards optimal allocation of computer resources: Trade-offs between uncertainty quantification, discretization and model reduction.
Environ. Model. Softw., 2013
2012
Data-driven uncertainty quantification using the arbitrary polynomial chaos expansion.
Reliab. Eng. Syst. Saf., 2012
2011
IEEE Trans. Vis. Comput. Graph., 2011