Data Science Research Group

Who we are


We conduct research on the application and development of Machine Behaviour and Artificial Intelligence. The Data Science Research Group cooperates closely with the Data Science study programme at the University of Applied Sciences Zwickau (WHZ).

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Research Results

The following cards show some of our research results, especially some of our software projects.


Tensor-Calculus (TC)

Python 3.8+
Version Unreleased

TC is a scientific computing library for machine learning. TC establishes practical access to neural tensor formats (NTF). NTF have many applications in all fields of machine learning, where machine learning mainly deals with function approximations.

This project is currently under heavy development and will be released soon. If you would like to request beta access, please send us an e-mail to etshAgi.{xjdlbv/ef

Discrete Optimization Extension (DOpE)

Python 3.8+
Version Unreleased

A library for solving Discrete Minimization Problems. Dope provides Methods like AdaptiveCrossSearch, BayesSearch, GridSearch and RandomSearch. It is used for model optimization.

This project is currently under heavy development and will be released soon. If you would like to request beta access, please send us an e-mail to etshAgi.{xjdlbv/ef

Bias Variance Agent (BiVA)

Python 3.8+
Version Unreleased

Biva library serves as a tool to handle bias-variance tradeoff while solving supervised learning problems. Agent provides API-independent approach for model exploration, evaluation and hyperparameter optimisation.

This project is currently under heavy development and will be released soon. If you would like to request beta access, please send us an e-mail to etshAgi.{xjdlbv/ef

The Team

These are the people working in our research group.


Prof. Dr. rer. nat. Mike Espig
research director

"Tamer of the Algorithms"

  • Data Science
  • Development of Methods for Machine Learning and Artificial Intelligence
  • Analysis and Numerics
  • Numerical Treatment of High Dimensional Problems by Means of Tensor Format Representations
  • Mathematics for Engineers and in the Sciences
  • since 3/2017
    Professor of Mathematics at WHZ
  • 04/2014-02/2017
    Professor of Numerical and Applied Analysis at RWTH Aachen
  • 10/2013-03/2014
    Researcher at TU Berlin, Prof. Dr. Harry Yserentant.
  • 01/2008-09/2013
    Researcher at Max Planck Institute for Mathematics in the Sciences, Leipzig, Prof. Dr. Dr. h.c. Hackbusch.
  • 04/2005-12/2007
    PhD Student at the Max Planck Institute for Mathematics in the Sciences, Leipzig, Supervisor Prof. Dr. Dr. h.c. W. Hackbusch
Antje Holtz
Antje Holtz
public relations manager

"Tweeter"

Christian Ahlswede
Christian Ahlswede
student assistant
Christian Walter
Christian Walter
research assistant

"Current Expert"

David Gadsch
David Gadsch
student assistant
Katsiaryna Radschanka
Katsiaryna Radschanka
student assistant
Kostiantyn Pysanyi
Kostiantyn Pysanyi
student assistant
Marcel Becker
Marcel Becker
research assistant

"Software Ninjaneer"

Michaela Banert
Michaela Banert
public relations manager
Tobias Haubold
Tobias Haubold
research assistant

"Lead Code Wizard"

Tommy Hartmann
Tommy Hartmann
research assistant

"Director of World Creation"

Research Projects

The following projects are an excerpt of our research work and funding.


KI-Lab-EmCo

KI-Lab, Efficent Methods of Conditional Monitoring

The aim of the project is to set up a holistic AI laboratory to use modern methods of condition monitoring by means of machine learning. Current methods as well as new methods using neural tensor formats are taken into account.

MoITra

Modular Intelligent Transport System in Intralogistics

The aim of the project is to develop a radio-based driverless transport system for intralogistics, which, due to the deliberate logic of tensor formats, can on the one hand be highly fail-safe and on the other hand quickly and adaptively handle new tasks.

Saxony5 - CCL KI

Saxony5 - Smart University Grid, CCL Artifical Intelligence

The aim of the project is the implementation of a co-creation lab (CCL) "Artificial Intelligence" in the joint project "Saxony5". This CCL is intended to promote regional exchange on the topics

Publications

This is an excerpt of our publications.


  • Iterative algorithms for the post-processing of high-dimensional data
    Published: January 2020 - Journal of Computational Physics, 410, 109396
    Authors: Mike Espig, Wolfgang Hackbusch, Alexander Litvinenko, Hermann G. Matthies, Elmar Zander
    Doi: 10.1016/j.jcp.2020.109396
    Link: https://www.sciencedirect.com
  • On the Convergence of Alternating Least Squares Optimisation in Tensor Format Representations
    Published: January 2015 - preprint
    Authors: Mike Espig, Wolfgang Hackbusch, Aram Khachatryan
    Arxiv: 1506.00062
    Link: https://www.igpm.rwth-aachen.de
  • Convergence of Alternating Least Squares Optimisation for Rank-One Approximation to High Order Tensors
    Published: January 2014 - preprint
    Authors: Mike Espig, Aram Khachatryan
    Arxiv: 1503.05431
    Link: https://www.igpm.rwth-aachen.de
  • Efficient low-rank approximation of the stochastic Galerkin matrix in tensor formats
    Published: January 2014 - Computers & Mathematics with Applications, 67(4), 818-829
    Authors: Mike Espig, Wolfgang Hackbusch, Alexander Litvinenko, Hermann G. Matthies, Philipp Wähnert
    Doi: 10.1016/j.camwa.2012.10.008
    Link: https://www.mis.mpg.de
  • Variational Calculus with Sums of Elementary Tensors of Fixed Rank
    Published: January 2012 - Numerische Mathematik, 122(3), 469-488
    Authors: Mike Espig, Wolfgang Hackbusch, Thorsten Rohwedder, Reinhold Schneider
    Doi: 10.1007/s00211-012-0464-x
    Link: https://www.mis.mpg.de
  • Efficient Analysis of High Dimensional Data in Tensor Formats
    Published: January 2012 - In Sparse Grids and Applications (pp. 31-56). Springer, Berlin, Heidelberg
    Authors: Mike Espig, Wolfgang Hackbusch, Alexander Litvinenko, Hermann G. Matthies, Elmar Zander
    Doi: 10.1007/978-3-642-31703-3_2
    Link: https://www.mis.mpg.de
  • A Regularized Newton method for the Efficient Approximation of Tensors Represented in the Canonical Tensor Format
    Published: January 2012 - Numerische Mathematik, 122(3), 489-525
    Authors: Mike Espig, Wolfgang Hackbusch
    Doi: 10.1007/s00211-012-0465-9
    Link: https://www.mis.mpg.de
  • A note on approximation in Tensor Chain format
    Published: January 2012 - Computing and Visualization in Science, 15(6), 331-344
    Authors: Mike Espig, Kishore Kumar Naraparaju, Jan Schneider
    Doi: 10.1007/s00791-014-0218-7
    Link: https://www.mis.mpg.de
  • Optimization Problems in Contracted Tensor Networks
    Published: January 2011 - Computing and visualization in science, 14(6), 271-285
    Authors: Mike Espig, Wolfgang Hackbusch, Stefan Handschuh, Reinhold Schneider
    Doi: 10.1007/s00791-012-0183-y
    Link: https://www.mis.mpg.de
  • Black Box Low Tensor Rank Approximation using Fibre-Crosses
    Published: January 2009 - Constructive approximation, 30(3), 557
    Authors: Mike Espig, Lars Grasedyck, Wolfgang Hackbusch
    Doi: 10.1007/s00365-009-9076-9
    Link: https://www.mis.mpg.de

  • Tensor Representation Techniques for Full Configuration Interaction: A Fock Space Approach Using the Canonical Product Format
    Published: January 2016 - The Journal of chemical physics, 144(24), 244102
    Authors: Karl-Heinz Böhm, Mike Espig, Alexander A. Auer
    Doi: 10.1063/1.4953665
    Link: https://www.igpm.rwth-aachen.de
  • Mesh-free canonical tensor products for six-dimensional density matrix: computation of kinetic energ
    Published: January 2016 - Computing and Visualization in Science, 17(6), 267-275
    Authors: Sambasiva Rao Chinnamsetty, Mike Espig, Wolfgang Hackbusch
    Doi: 10.1007/s00791-016-0263-5
    Link: https://www.mis.mpg.de
  • Tensor Representation Techniques in post-Hartree Fock Methods: Matrix Product State Tensor Format
    Published: January 2013 - Molecular physics, 111(16-17), 2398-2413
    Authors: Udo Benedikt, Henry Auer, Mike Espig, Wolfgang Hackbusch, Alexander Auer
    Doi: 10.1080/00268976.2013.798433
    Link: https://www.mis.mpg.de
  • Tensor Decomposition in post-Hartree Fock Methods
    Published: January 2011 - The journal of chemical physics, 134(5), 054118
    Authors: Udo Benedikt1, Alexander A. Auer, Mike Espig, Wolfgang Hackbusch
    Doi: 10.1063/1.3514201
    Link: https://www.mis.mpg.de
  • Canonical tensor products as a generalization of Gaussian-type orbitals
    Published: January 2010 - International journal of research in physical chemistry and chemical physics, 224(3-4), 681-694
    Authors: Sambasiva Rao Chinnamsetty, Mike Espig, Heinz-Jürgen Flad, Wolfgang Hackbusch
    Doi: 10.1524/zpch.2010.6131
    Link: https://www.mis.mpg.de
  • Tensor product approximation with optimal rank in quantum chemistry
    Published: January 2007 - The journal of chemical physics, 127(8), 084110
    Authors: Sambasiva Rao Chinnamsetty, Mike Espig, Boris N. Khoromskij, Wolfgang Hackbusch
    Doi: 10.1063/1.2761871
    Link: https://www.mis.mpg.de

  • On the Robustness of Elliptic Resolvents Computed by means of the Technique of Hierarchical Matric
    Published: January 2008 - Applied Numerical Mathematics, 58(12), 1844–1851
    Authors: Mike Espig, Wolfgang Hackbusch
    Doi: 10.1016/j.apnum.2007.11.006
    Link: https://www.mis.mpg.de

Our Partners

Here are our partners who support us in our work.