Learning Models from Data:
Model Reduction, System Identification and Machine Learning
GAMM Juniors' Summer School on Applied Mathematics and Mechanics
July 27 - 31, 2020
Objectives and Topics
The aim of this summer school is to study recent developments in the area of learning models from data, which will be presented by three top-level experts in lecture and exercise classes. The combination and interplay of different techniques from physics-based modeling, data-driven modeling, model reduction, system identification and machine learning techniques shall bring together researchers from different disciplines.
In particular, the summer school is tailored for young researchers, i.e. master students in their final phase, PhD students and post-doctoral researchers.
Each participant is invited to present a poster on his/her own research with the emphasis on how learning techniques are used or are intended to be used.
The summer school will be held virtually. All participants will get access to the virtual lectures, exercise courses and discussions.
A poster of this event can be found here.
Application and Registration
We invite young researchers from disciplines related to the topic of the school to apply. For this, please submit a short cover letter describing your motivation to participate and your experience in the field (if already existing). Moreover, please provide a short abstract for a poster with emphasis on how your research topic is using or how you intend to use machine learning techniques. The submission has to be done via our Indico page and will be open from March 23, 2020. The deadline for application is June 19, 2020.
The decision about acceptance will be communicated by the end of June 2020. The selected participants will then be able to register for the event. There is no registration fee.
Lectures and exercise courses are given by
- J. Nathan Kutz (University of Washington)
- codes (zip, 4 KB)
- Benjamin Peherstorfer (New York University)
- slides (pdf, 24 MB)
- Feliks Nüske (Paderborn University)
If you have any questions, please send an e-mail to: firstname.lastname@example.org
The summer school starts on July 27, 2020 and ends on July 31, 2020. The program of the summer school is available at our Indico page.
The summer school will be held virtually. There will be no in-person meetings.
The participants can take part in a virtual social event on July 28, 2020.
Virtual Group Photo
Publications PAMM Special Issue
All participants of the SAMM 2020 can submit either a proceeding (without page limitation) or a poster or both to PAMM (Proceedings in Applied Mathematics and Mechanics) SAMM 2020 Special Issue. The deadline for submission is 15 October 2020 31 October 2020. The editors reserve the rights to deny publication of a submitted manuscript or poster based on the reviewer's decision. All submissions need to be created in accordance to the guidelines of Wiley.
For submission, please follow the instructions as outlined and use the template files provided by PAMM Wiley. All contributions (poster or proceedings) have to be submitted via the Wiley ScholarOne Manuscripts system. Please select "SAMM 2020 GAMM Juniors" as conference in the submission process. If you have any questions concerning the submission process, please contact PAMM Wiley.
Sponsors and Support
GAMM Juniors' Summer Schools
The GAMM Juniors' Summer Schools on Applied Mathematics and Mechanics (SAMMs) are organized by the GAMM Juniors. Previous, current and upcoming editions of the SAMMs are
- SAMM 2021: Shape and Topology Optimization (Graz)
- SAMM 2020: Learning Models from Data (Magdeburg)
- SAMM 2019: Space-time FEMs for parabolic and hyperbolic conservation laws (Hannover)
- SAMM 2017: Bayesian Inference: Probabilistic Learning from Data (Braunschweig)
- SAMM 2016: Geometric Methods in Multi-Body and Structural Dynamics (Grimma)
- SAMM 2016: Energy Based Modeling, Simulation, and Control of Complex Physical Systems (Berlin)
- SAMM 2015: Materials with Discontinuities (Stuttgart)
- SAMM 2014: Differential-Algebraic Equations (Elgersburg)