Staff Dr. Bastian Bohn

Address:
Institut für Numerische Simulation
Friedrich-Hirzebruch-Allee 7
53115 Bonn
Phone: +49 228 73-69813
Office: FHA7 3.005
E-Mail: ed tod nnob-inu tod sni ta nhoba tod b@foo tod de

News

Teaching

Winter semester 2024/25

Summer semester 2024

See teaching activities of the whole group.

Research Projects

Current

Multilevel sparse tensor product approximation for manifolds and for functions and operators on manifolds

Project C04, DFG SFB 1060.

Homepage.

Completed

SIMDATA-NL: Nichtlineare Charakterisierung und Analyse von FEM-Simulationsergebnissen für Autobauteile und Crash-Tests

BMBF support program.

Homepage.

Publications

Contributed talks

  1. A representer theorem for deep kernel learning. B. Bohn. Contributed talk at ENUMATH19 - https://www.enumath2019.eu/ - European Numerical Mathematics and Advanced Applications Conference 2019, Egmond aan Zee, Netherlands, September 30 - October 4, 2019. BibTeX
  2. Detecting hidden structure with deep kernel learning. B. Bohn. Contributed talk at HDA19 - https://math.ethz.ch/sam/news-and-events/conferences-and-workshops/8th-workshop-on-high-dimensional-approximation.html - 8th Workshop on High-Dimensional Approximation, Zurich, Switzerland, September 9-13, 2019. BibTeX
  3. Least squares regression on sparse grids. B. Bohn. Invited talk at ASCW01 - Workshop on challenges in optimal recovery and hyperbolic cross approximation https://www.newton.ac.uk/event/ascw01, Isaac Newton Institute for Mathematical Sciences, Cambridge, UK, February 18-22, 2019. BibTeX
  4. Optimal data transformation for sparse grids. B. Bohn. Contributed talk at SGA18 - https://www5.in.tum.de/SGA2018/index.php - 5th Workshop on Sparse Grids and Applications, Munich, Germany, July 23 -27, 2018. BibTeX
  5. Error bounds for regularized least-squares regression on finite-dimensional function spaces. B. Bohn. Contributed talk at UQ16 - https://www.siam.org/meetings/uq16 - SIAM Conference on Uncertainty Quantification, Lausanne, Switzerland, April 5-8, 2016. BibTeX
  6. Sparse grid regression in the noiseless setting. B. Bohn. Contributed talk at SGA16 - http://www.csm.ornl.gov/workshops/SGA2016 - 4th Workshop on Sparse Grids and Applications, Miami, FL, USA, October 4-7, 2016. BibTeX
  7. Convergence results for discretized regression applied to sparse grids. B. Bohn. Contributed talk at SGA14 - https://ipvs.informatik.uni-stuttgart.de/sgs/SGA2014 - 3rd Workshop on Sparse Grids and Applications, Stuttgart, Germany, September 1-5, 2014. BibTeX
  8. Hierarchical dimension-adaptive machine learning. B. Bohn. Contributed talk at MCQMC14 - http://mcqmc2014.cs.kuleuven.be - Eleventh International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing, Leuven, Belgium, April 6-11, 2014. BibTeX
  9. On dimensionality reduction for high-dimensional machine learning with sparse grids. B. Bohn. Contributed talk at HDA13 - http://hda2013.ins.uni-bonn.de - 5th Workshop on High-Dimensional Approximation, Canberra, Australia, February 11-15, 2013. BibTeX
  10. Adaptive sparse grid discretizations for high-dimensional manifold learning tasks. B. Bohn. Contributed talk at DWCAA12 - http://events.math.unipd.it/dwcaa2012 - 3rd Dolomites Workshop on Constructive Approximation and Applications, Alba di Canazei, Italy, September 9-14, 2012. BibTeX
  11. Principal manifold learning with a dimension-adaptive sparse grid discretization. B. Bohn. Contributed talk at SGA12 - http://www5.in.tum.de/SGA2012 - 2nd Workshop on Sparse Grids and Applications, Munich, Germany, July 2-6, 2012. BibTeX
  12. An adaptive sparse grid approach to time series prediction. B. Bohn. Contributed talk at SGA11 - http://www.him.uni-bonn.de/programs/past-programs/past-trimester-programs/analysis-and-numerics-for-high-dimensional-problems/workshop-1-sparse-grids-and-applications/ - HIM Trimester Program on Analysis and Numerics for High Dimensional Problems: Workshop on Sparse Grids and Applications, Bonn, Germany, May 16-20, 2011. BibTeX

Poster presentations

  1. A representer theorem for deep kernel learning. B. Bohn. Poster at BDHPC18 - http://www.ipam.ucla.edu/programs/workshops/workshop-i-big-data-meets-large-scale-computing - IPAM/UCLA Workshop: Big Data Meets Large-Scale Computing, Los Angeles, CA, USA, September 24 - 28, 2018. BibTeX
  2. A representer theorem for deep kernel learning. B. Bohn. Poster at DS3 - http://2017.ds3-datascience-polytechnique.fr - Data Science Summer School, Paris, France, August 28 - September 1, 2017. BibTeX
  3. SIMDATA-NL: Nichtlineare Charakterisierung und Analyse von FEM-Simulationsergebnissen für Autobauteile und Crash-Tests. B. Bohn. Poster at BMBF status seminar - Mathematik für Innovationen in Industrie und Dienstleistungen, Bonn, Germany, June 20-21, 2013. BibTeX

Other talks

  1. Orthogonal transformations for data-driven sparse grid algorithms. B. Bohn. Public seminar talk - http://www.ipam.ucla.edu/programs/long-programs/science-at-extreme-scales-where-big-data-meets-large-scale-computing/?tab=seminar-series - IPAM/UCLA Long Program: Science at Extreme Scales: Where Big Data Meets Large-Scale Computing - Seminar Series, Los Angeles, CA, USA, October 23, 2018. BibTeX
  2. On the best approximation error of energy sparse grids in H1H^1. B. Bohn. Public seminar talk - https://ins.uni-bonn.de/group/neitzel/page/seminar - Institute for Numerical Simulation, Mathematics of Computation, Seminar Series, Bonn, Germany, November 9, 2017. BibTeX
  3. SIMDATA-NL: Nichtlineare Charakterisierung und Analyse von FEM-Simulationsergebnissen für Autobauteile und Crash-Tests. B. Bohn. Talk at BMBF status seminar - Mathematik für Innovationen in Industrie und Dienstleistungen, Bonn, Germany, June 20-21, 2013. BibTeX