Prof. Dr. rer. nat. Mike Espig

Leiter der Data Science Research Group

Studiengang Data Science

Sprechzeiten

nach Vereinbarung

Anschrift

Westsächsische Hochschule Zwickau
Fakultät Physikalische Technik/Informatik
Fachgruppe Mathematik
PSF 201037
D 08012 Zwickau

 

Lehr- und Forschungsgebiete

Mathematik für Ingenieure
Analysis und Numerik
Numerik hochdimensionaler Probleme mittels Tensorformate

Akademischer Werdegang

seit 3/2017
Professor für Mathematik, Westsächsischen Hochschule Zwickau, Fakultät Physikalische Technik/
Informatik

4/2014-2/2017
Professor für Numerische und Angewandte Analysis, Rheinisch-Westfälische
Technische Hochschule Aachen (RWTH Aachen), Institut für Geometrie und Praktische Mathematik

10/2013– 3/2014
Wissenschaftlicher Mitarbeiter, Technische Universität Berlin, Institut für Mathematik,
Numerische Analysis partieller Differentialgleichungen, Prof. Dr. Harry Yserentant.

1/2008–9/2013
Wissenschaftlicher Mitarbeiter, Max-Planck-Institut für Mathematik in den
Naturwissenschaften, Leipzig, Wissenschaftliches Rechnen, Prof. Dr. Dr. h.c. W. Hackbusch.

04/2005–12/2007
Promotion zum Dr. rer. nat. im Fachgebiet Mathematik, Max-Planck-Institut
für Mathematik in den Naturwissenschaften, Effiziente Bestapproximation mittels
Summen von Elementartensoren in hohen Dimensionen, Betreuer: Prof. Dr. Dr. h.c. W. Hackbusch.

1999–2004
Studium der Mathematik und Physik im Nebenfach, Dipl.-Math., Christian-
Albrechts-Universität, Kiel, Approximation von Resolventen des Laplace-Operators
mit Hilfe hierarchischer Matrizen, Betreuer: Prof. Dr. Dr. h.c. W. Hackbusch.

Ausgewählte Vorträge

2018 Anaheim, SIAM Conference on Uncertainty Quantification (UQ18), Low-Rank Tensors for
Stochastic Forward Problems

2017 WIAS, Berlin, Workshop on Mathematics of Deep Learning 2017, An Effcient Method for Statistical Learning by Means of Tensor Format
Representations

2016 BIRS, Banff, The Numerical Treatment of High Dimensional Problems by Means of Tensor Format Representations

2016 San Servolo, Venice, The Convergence of Alternating Steepest Descent Optimisation in Tensor Format Representations

2015 SIAM CSE, Salt Lake City, Tensor Format Representations and Optimal Model
Reduction for Uncertainty Quantification.

2014 TU Berlin, The Treatment of High Dimensional Problems by Means of Tensor Format
Representations.

2014 Oberwolfach, On the Convergence of Alternating Least Squares Optimisation in
Tensor Format Representations.

2013 Oberwolfach, The Numerical Treatment of Partial Differential Equations with Stochastic
Coefficients by Means of Tensor Format Representation.

2013 HDA 2013, ANU Canberra, Alternating Least Squares Optimisation in Tensor
Format Representations.

2012 GAMM-Jahrestagung, Darmstadt, On the Convergence of Alternating Least
Squares Optimisation in Tensor Format Representations.

2011 GAMM-Jahrestagung, Graz, Treatment of High Dimensional Problems by Means
of Tensor Networks.

2011 HIM, Bonn, Tensor Networks.

2010 ILAS, Pisa, Optimisation Problems in Tensor Networks.

2009 GAMM-Jahrestagung, Gdansk, On the Efficient Treatment of High Dimensional
Problems by Means of Elementary Tensor Sums.

2009 USC, Los Angeles, Efficient Treatment of High Dimensional Problems.

2008 SIAM-Jahrestagung, San Diego, Efficient Best-Approximation of Tensor-Sums
and Applications in High Dimensions.

2007 ENUMATH, Graz, Approximation of Tensor-Sums in High Dimensions with Application
to Multi-Dimensional Operators.

2007 Nonlinear and Adaptive Approximation in High Dimensions, Bad Honnef,
Efficient Best-Approximation of Tensor-Sums and Applications.

Zur Veröffentlichung eingereichte Artikel

The Alternating Steepest Descent Method for Solving Linear Systems in Tensor Format Representations, M. Espig.

An Efficient Method for Statistical Learning by Means of Tensor Format Representations, M. Espig.

Ausgewählte Artikel

S.R. Chinnamsetty, M. Espig, B.N. Khoromskij, W. Hackbusch, H.J. Flad, et al. Tensor
product approximation with optimal rank in quantum chemistry. J. Chem. Phys,
127(8):84110–84110, 2007.

M. Espig and W. Hackbusch. On the robustness of elliptic resolvents computed by
means of the technique of hierarchical matrices. Appl. Numer. Math., 58(12):1844–1851,
December 2008.

M. Espig, L. Grasedyck, and W. Hackbusch. Black box low tensor-rank approximation
using fiber-crosses. Constructive approximation, 30(3):557–597, 2009.

S.R. Chinnamsetty, M. Espig, H.J. Flad, and W. Hackbusch. Canonical tensor products
as a generalization of gaussian-type orbitals. Journal of Research in Physical Chemistry
and Chemical Physics, 224(3-4):681–694, 2010.

U. Benedikt, A.A. Auer, M. Espig, and W. Hackbusch. Tensor decomposition in posthartree-
fock methods. i. two-electron integrals and mp2. J. Chem. Phys, 134(5):4118,
2011.

Mike Espig, Wolfgang Hackbusch, Stefan Handschuh, and Reinhold Schneider. Optimization
problems in contracted tensor networks. Computing and Visualization in
Science, 14:271–285, 2011.

Mike Espig, Wolfgang Hackbusch, Thorsten Rohwedder, and Reinhold Schneider.
Variational calculus with sums of elementary tensors of fixed rank. Numerische
Mathematik, 122:469–488, 2012.

Mike Espig and Wolfgang Hackbusch. A regularized newton method for the efficient
approximation of tensors represented in the canonical tensor format. Numerische
Mathematik, 122:489–525, 2012.

Mike Espig, Wolfgang Hackbusch, Alexander Litvinenko, Hermann G. Matthies, and
Elmar Zander. Efficient analysis of high dimensional data in tensor formats. In Jochen
Garcke and Michael Griebel et al., editors, Sparse Grids and Applications, volume 88
of Lecture Notes in Computational Science and Engineering, pages 31–56. Springer
Berlin Heidelberg, 2013.

Mike Espig, Wolfgang Hackbusch, Alexander Litvinenko, Hermann G. Matthies, and
Philipp Wähnert. Efficient low-rank approximation of the stochastic galerkin matrix
in tensor formats. Computers and Mathematics with Applications, November 2012.

Udo Benedikt, Henry Auer, Mike Espig, Wolfgang Hackbusch, and Alexander A. Auer.
Tensor representation techniques in post-Hartree-Fock methods : matrix product state
tensor format. Molecular Physics, 111(16/17):2398–2413, 2013.

Sambasiva Rao Chinnamsetty, Mike Espig, and Wolfgang Hackbusch. Mesh-free
canonical tensor products for six-dimensional density matrix : Computation of Kinetic
Energy in Electronic Structure Calculations. 2013.

K. H. Böhm, A.A. Auer, and M. Espig. Tensor representation techniques for full
configuration interaction: A fock space approach using the canonical product format.
J. Chem. Phys, 144, 2016.