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Philipp Trunschke
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2020 – today
- 2024
- [i11]Philipp Trunschke, Anthony Nouy:
Almost-sure quasi-optimal approximation in reproducing kernel Hilbert spaces. CoRR abs/2407.06674 (2024) - [i10]Philipp Trunschke, Anthony Nouy:
Optimal sampling for least squares approximation with general dictionaries. CoRR abs/2407.07814 (2024) - 2023
- [j4]Christian Bayer
, Martin Eigel, Leon Sallandt
, Philipp Trunschke
:
Pricing High-Dimensional Bermudan Options with Hierarchical Tensor Formats. SIAM J. Financial Math. 14(2): 383-406 (2023) - [j3]Martin Eigel, Nando Farchmin, Sebastian Heidenreich, Philipp Trunschke:
Adaptive Nonintrusive Reconstruction of Solutions to High-Dimensional Parametric PDEs. SIAM J. Sci. Comput. 45(2): 457- (2023) - [i9]Philipp Trunschke, Anthony Nouy, Martin Eigel:
Weighted sparsity and sparse tensor networks for least squares approximation. CoRR abs/2310.08942 (2023) - 2022
- [i8]Philipp Trunschke:
Convergence bounds for nonlinear least squares for tensor recovery. CoRR abs/2208.10954 (2022) - 2021
- [j2]Michael Götte, Reinhold Schneider, Philipp Trunschke:
A Block-Sparse Tensor Train Format for Sample-Efficient High-Dimensional Polynomial Regression. Frontiers Appl. Math. Stat. 7: 702486 (2021) - [i7]Christian Bayer, Martin Eigel, Leon Sallandt, Philipp Trunschke:
Pricing high-dimensional Bermudan options with hierarchical tensor formats. CoRR abs/2103.01934 (2021) - [i6]Michael Götte, Reinhold Schneider, Philipp Trunschke:
A block-sparse Tensor Train Format for sample-efficient high-dimensional Polynomial Regression. CoRR abs/2104.14255 (2021) - [i5]Martin Eigel, Nando Farchmin, Sebastian Heidenreich, Philipp Trunschke:
Efficient approximation of high-dimensional exponentials by tensornetworks. CoRR abs/2105.09064 (2021) - [i4]Philipp Trunschke:
Convergence bounds for nonlinear least squares and applications to tensor recovery. CoRR abs/2108.05237 (2021) - [i3]Martin Eigel, Nando Farchmin, Sebastian Heidenreich, Philipp Trunschke:
Adaptive non-intrusive reconstruction of solutions to high-dimensional parametric PDEs. CoRR abs/2112.01285 (2021) - 2020
- [i2]Martin Eigel, Reinhold Schneider, Philipp Trunschke:
Convergence bounds for empirical nonlinear least-squares. CoRR abs/2001.00639 (2020)
2010 – 2019
- 2019
- [j1]Martin Eigel, Reinhold Schneider, Philipp Trunschke
, Sebastian Wolf:
Variational Monte Carlo - bridging concepts of machine learning and high-dimensional partial differential equations. Adv. Comput. Math. 45(5): 2503-2532 (2019) - [i1]Dominik Alfke, Weston Baines, Jan Blechschmidt, Mauricio J. del Razo Sarmina, Amnon Drory, Dennis Elbrächter, Nando Farchmin, Matteo Gambara, Silke Glas, Philipp Grohs, Peter Hinz, Danijel Kivaranovic, Christian Kümmerle, Gitta Kutyniok, Sebastian Lunz, Jan MacDonald, Ryan Malthaner, Gregory Naisat, Ariel Neufeld, Philipp Christian Petersen, Rafael Reisenhofer, Jun-Da Sheng, Laura Thesing, Philipp Trunschke, Johannes von Lindheim, David Weber, Melanie Weber:
The Oracle of DLphi. CoRR abs/1901.05744 (2019) - 2017
- [c1]Tom Streubel, Christian Strohm, Philipp Trunschke, Caren Tischendorf
:
Generic Construction and Efficient Evaluation of Flow Network DAEs and Their Derivatives in the Context of Gas Networks. OR 2017: 627-632
Coauthor Index
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last updated on 2024-08-17 23:42 CEST by the dblp team
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