NEWS: The picture gallery is now online for participants: morml2016-gallery.
Description and Scope
Model reduction has developed into an active and interdisciplinary research field, which primarily aims at providing accurate approximations of high dimensional simulation models. The reduced models often achieve orders of magnitude reduction in computational complexity for multi-query and real-time applications such as control, optimization, inference, and uncertainty quantification. This workshop aims at demonstrating the significant overlap between data-driven model reduction and machine learning. In particular, recently a large number of model reduction methods have emerged that rely on machine learning techniques such as feature extraction, clustering, kernel methods, and regression. The workshop brings together scientists and engineers interested in recent developments of data-driven model reduction, machine learning, and the combination and connection between these two fields.
Topics of interest...
... include, but are not limited to
Data and model reduction: Loewner approach, data-driven methods, data assimilation, state estimation of noisy systems, Kalman filtering
Machine learning and model reduction: Greedy procedures, adaptivity/localization, clustering, manifold learning, nonlinear approximations, regression, kernel methods, error surrogates
Analysis: stability analysis, conservation of physical properties, error quantification and convergence
Applications: optimization/control, UQ, inference; circuit, CFD, mechanics, and finance simulations; software development and industrial application aspects
- Abstract submission deadline:
December 15, 2015
December 31, 2015, 24:00h (Central European Time)
- Author notification:
January 15, 2016
- Early bird registration:
January 31, 2016
- Late online registration deadline:
March 20, 2016
On-site registration during the workshop will be possible if there are places left after the online registration deadline.
- 180 € - PhD Students (with studentship confirmation)
- 230 € - Participants from Academia
- 400 € - Participants with Industry Affiliation
The registration fee includes the lunches, coffee-breaks and the poster session. Note: The dinner is booked out. Dinner participation is no longer possible unless other registered participants refrain from their dinner participation.
To be eligible for the student rate, we request a proof of the student status as a pdf-file to be uploaded during your registration via this website.
The late registraton fees (from February 1, 2016 until March 20, 2016) consist of an addition of 100 EUR to the above amounts.
Funded by the SimTech Cluster on Simulation Technology at the University of Stuttgart and the COST TD1307 Action "European Model Reduction Network (EU-MORNET)".
- Christopher A. Beattie (Virginia Tech, USA)
- Kevin T. Carlberg (Sandia National Laboratories, USA)
- Yvon Maday (Université Pierre et Marie Curie, France)
- John Shawe-Taylor (University College London)