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Selected Recent Applications of Sparse Grids

B. Peherstorfer, C. Kowitz, D. Pflüger, and H. Bungartz. Numerical mathematics : theory, methods and applications, 8 (1): 47-77 (2015)
DOI: 10.4208/nmtma.2015.w05si

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Benjamin Rothaupt

Dr. phil. Benjamin Holfelder University of Stuttgart

Benjamin Bursik University of Stuttgart

Benjamin Kaiser University of Stuttgart

Dr. Benjamin Aberle University of Stuttgart

Other publications of authors with the same name

Online Adaptive Model Reduction for Nonlinear Systems via Low-Rank Updates.B. Peherstorfer, and K. Willcox. SIAM J. Scientific Computing, (2015)Fast Insight into High-Dimensional Parametrized Simulation Data.D. Butnaru, B. Peherstorfer, H. Bungartz, and D. Pflüger. ICMLA (2), page 265-270. IEEE, (2012)978-1-4673-4651-1.Density Estimation with Adaptive Sparse Grids for Large Data Sets.B. Peherstorfer, D. Pflüger, and H. Bungartz. SDM, page 443-451. SIAM, (2014)Multifidelity Monte Carlo Estimation with Adaptive Low-Fidelity Models.B. Peherstorfer. SIAM/ASA J. Uncertain. Quantification, 7 (2): 579-603 (2019)A Sparse-Grid-Based Out-of-Sample Extension for Dimensionality Reduction and Clustering with Laplacian Eigenmaps.B. Peherstorfer, D. Pflüger, and H. Bungartz. Australasian Conference on Artificial Intelligence, volume 7106 of Lecture Notes in Computer Science, page 112-121. Springer, (2011)Image Segmentation with Adaptive Sparse Grids.B. Peherstorfer, J. Adorf, D. Pflüger, and H. Bungartz. Australasian Conference on Artificial Intelligence, volume 8272 of Lecture Notes in Computer Science, page 160-165. Springer, (2013)Classification with Probability Density Estimation on Sparse GridsB. Peherstorfer, F. Franzelin, D. Pflüger, and H. Bungartz. Sparse Grids and Applications - Munich 2012, volume 97 of Lecture Notes in Computational Science and Engineering, page 255--270. Springer International Publishing, (January 2014)Density Estimation with Adaptive Sparse Grids for Large Data SetsB. Peherstorfer, D. Pflüger, and H. Bungartz. Proceedings of the 2014 SIAM International Conference on Data Mining, page 443--451. SIAM, (January 2017)Spatially adaptive sparse grids for high-dimensional data-driven problemsD. Pflüger, B. Peherstorfer, and H. Bungartz. Journal of Complexity, 26 (5): 508--522 (Oktober 2010)Model order reduction of parametrized systems with sparse grid learning techniques.B. Peherstorfer. Technical University Munich, (2013)