Events at and around the MCML

Matthias Schmid. University of Bonn.

Abstract: The talk introduces a regression model termed ”extended GB2 model”, which is designed to analyze ratios of biomarkers in epidemiological and medical research.

LMU Munich

The GDSD bring together data scientists from various fields with the aim to identify and discuss new methods, explore new fields of application, and enhance the professional image of data scientists.

René Vidal. John Hopkins University.

Abstract: There is a significant interest in developing ML algorithms whose final predictions can be explained in terms understandable to a human. To address this challenge, we develop a method for constructing high performance ML algorithms which are explainable by design.

Deutsches Museum in Munich

Happy and proud to be a part of this at Munich Center for Machine Learning - we will be present on stage with our directors, with talks by PIs, a stand, and a lot more.

Are you interested in the latest advancements and research trends in human augmentation? Join us for the “Workshop on Interaction with Technologies for Human Augmentation” organized by LMU Munich and HumaneAI, co-organized by MCML.

Gesine Reinert. University of Oxford.

Abstract: Networks are often used to represent complex dependencies in data, and network models can aid the understanding of such dependencies. This talk will present network models. We shall introduce a kernelized goodness of fit test (which is based on Stein’s method), give performance guarantees, and illustrate its use.

Polina Golland. Massachusetts Institute of Technology.

Abstract: We propose and demonstrate a novel approach to training image classification models based on large collections of images with limited labels. We take advantage of availability of radiology reports to construct joint multimodal embedding that serves as a basis for classification. We demonstrate the advantages of this approach in application to assessment of pulmonary edema severity in congestive heart failure that motivated the development of the method.

Konstantin Hopf. University of Bamberg.

Abstract: The current developments relating to the energy transition (decarbonization, decentralization, electrification of heat and mobility) pose particular challenges for the distribution grids and make accurate load forecasts increasingly important. Novel modeling approaches like the Transformer approach have proven to be promising architectures of neural networks for sequence data. The temporal fusion transformer (TFT) architecture seems particularly suitable for time series data to obtain high quality forecasts. To date, there are only a handful of studies that apply this approach to the electricity load forecasting problem, mostly in combination with other analytical approaches. Therefore, examine the performance of the TFT on short-term forecasting problems in the distribution grid.

Matt Wand. University of Technology Sydney.

Uta Hauck-Thum, Jochen Weller, Jochen Kuhn, Frauke Kreuter, Hinrich Schütze, Albrecht Schmidt. LMU.

Peter Flach. University of Bristol.

Laura Busse. Munich Center for NeuroSciences.
Frederick Klausche. LMU Institute of Pathology.
Björn Menze. UZH Department of Quantitative Biomedicine.

Moderation:  Michael Ingrisch (LMU), Björn Ommer (LMU).

Karl-Peter Hopfner. Gene Center and Department of Biochemistry (LMU).
Alexander Pritzel. DeepMind.

Moderation:  Julia Merlot (Spiegel).

Farinaz Koushanfar. UC San Diego.

Paulina Pankowska. Universiteit Utrecht.

Ron Kikinis. Harvard Medical School.

The Munich Center for Machine Learning is organizing together with impACTup! and ZD.B / LMU Media Informatics Group this two-part event, where we aim to shift researchers and students in Machine Learning and Artificial Intelligence into an Entrepreneurial Mindset. With input from experts and hands-on experience, we want to highlight the chances and risks that a career as a founder and entrepreneur can hold in contrast to research.

Björn Ommer, Bernd Bischl, Gitta Kutyniok, Markus Lerch, Michael Ingrisch, Fady Albashiti, Thomas Gudermann, Nikolaos Koutsouleris, Guillaume Landry, Johanna Klughammer, Anne-Laure Boulesteix. MCML, NVIDIA, LMU Klinikum.

Maggie Makar. University of Michigan.

Dr. Erik Curiel. Munich Center for Mathematical Philosophy (LMU).
Prof. Dr. Dieter Lüst. Professor of Mathematical Physics (LMU).
Dr. Marlene Weiß. Head of Science Department Süddeutsche Zeitung.

Andreas Joseph. Bank of England, London.

Jessica Vitak, Leah von der Heyde, Zothan Mawii, Markus Herklotz, Vasilka Stovilova, Alena Buyx, Kobbi Nissim, Philipp Räther. BERD@NFDI, TAPP, LMU.

Moderation:  Frauke Kreuter (LMU).

Fabiana Zollo. Ca'Foscari University of Venice.

Andy Guess. Princeton University.

Rianne de Heide. Vrije Universiteit Amsterdam.

Alex Smola. VP & Distinguished Scientist at Amazon Web Services.

Foster Provost. New York University.

Giacomo De Nicola, Cornelius Fritz, Göran Kauermann. Institut für Statistik, LMU.

Barbara Plank, Mario Haim, Uli Köppen, Hinrich Schütze. LMU, LMU, AI und Automation Lab des BR, LMU.

Ingmar Weber. Saarland University.

Alexander Kreiß. Universität Leipzig.

Stephen Smith. University of Oxford.

Daniel Wilhelm. Institut für Statistik, LMU.

Markus Strohmaier. University of Mannheim.

Michael Bronstein. University of Oxford.

Daniel Gruen. LMU.
Lukas Heinrich. TUM.
Kevin Heng. LMU.

Moderation:  Jenny Sorce (Université Paris-Saclay).

A collaboration of Women in AI & Robotics, the University of Waterloo Department of Mechanical and Mechatronics Engineering, and Mila. For participants, we target the 18–25-year age group by reaching out to schools and Universities further to promote entry into the exciting field of robotics.

Christoph Jansen. Institut für Statistik, LMU.

Vince Madai. Berlin Institute of Health of Charité Berlin.

Max Welling. University of Amsterdam.

Stephane Mallat. College de France.

Bavarian Academy of Sciences and Humanities

Thomas Nagler. Institut für Statistik, LMU.

Susan Athey. Stanford University.

Hamsa Bastani. University of Pennsylvania.

Elizabeth Stuart. Johns Hopkins Bloomberg School of Public Health, Baltimore.

Tobias Hatt and Daniel Tschernutter. ETH Zurich.

Maria Eduarda Silva. Universität Porto.

Stefan Heyder. Technische Universität Illmenau.
Thomas Hotz. Technische Universität Illmenau.

Nathan Kallus. Cornell University.

Eimo Martens. TUM.
Narges Ahmidi. Helmholtz.

Kilian Weinberger. Cornell University.

Markus Gangl. Goethe-Universität Frankfurt.

Viktor Bengs. Department of Statistics, LMU Munich.

Daniel Neill. New York University.

Göran Kauermann. Department of Statistics, LMU Munich.

Hervé Delingette. INRIA.

Walter J. Rademacher. Department of Statistics, LMU Munich.

Florentina Bunea. Cornell University.

Cynthia Dwork. Harvard University.

Carolin Strobl. Universität Zurich.

Yifan Cui. National University Singapore.

Caroline Essert. University of Strasbourg, CNRS.

Polina Golland. Massachusetts Institute of Technology.

Benedikt Wiestler (TUM), Shadi Albarqouni (Helmholtz München).

Oliver Müller. Management Information Systems and Data Analytics, University of Paderborn.

Christian Heumann. Department of Statistics, LMU Munich.

Thomas Seidl. Professor für Informatik. Er ist Inhaber des Lehrstuhls für Datenbanksysteme und Data Mining an der Fakultät für Mathematik, Informatik und Statistik und Direktor des Munich Center for Machine Learning..

Malte Toetzke. Group of Sustainability and Technology, ETH Zurich.

Bernd Bischl. Department of Statistics, LMU Munich.

Professor Ron Kikinis. Harvard Medical School.

Benedikt Wiestler. TUM.
Shadi Albarqouni. Helmholtz München.

Helmut Küchenhoff. Professor für Mathematik am Institut für Statistik und Leiter des statistischen Beratungslabors an der LMU.

Daniel L. Oberski. Universität Utrecht.

Frauke Kreuter. Department of Statistics, LMU Munich.

Thomas Augustin. Department of Statistics, LMU Munich.

Daniel Grün. Inhaber des Lehrstuhls für Astrophysik, Kosmologie und Künstliche Intelligenz an der Fakultät für Physik der LMU.

Heribert Schunkert, Matthias Heining.

Sami Haddadin, Gitta Kutyniok, Eva Wolfangel.

Enrique Jiménez. Professor für altorientalische Literaturen am Institut für Assyriologie und Hethitologie an der Fakultät für Kulturwissenschaften der LMU.

Frauke Kreuter. Inhaberin des Lehrstuhls für Statistik und Data Science in den Sozial- und Humanwissenschaften und Co-Direktorin der Data Science Center an der University of Maryland und der Universität Mannheim..

Dirk Wilhelm, Nassir Navab.

Michael I. Jordan. Pehong Chen Distinguished Professor im Department of Electrical Engineering and Computer Sciences and Department of Statistics at the University of California, Berkeley.

The AutoML Fall School will cover core topics of AutoML, covering basics, state-of-the-art approaches and hands-on sessions. Enthusiastic AutoML experts will present their diverse views on AutoML to ML practitioners, developers, research engineers, researchers and students.

René Traue, Christian Lindenlaub. GfK, Nürnberg.

Timo von Oertzen. Universität der Bundeswehr München.

Stefan Feuerriegel. Fakultät für Betriebswirtschaftslehre, LMU.

LWDA, which expands to „Lernen, Wissen, Daten, Analysen“ („Learning, Knowledge, Data, Analytics“), covers recent research in areas such as knowledge discovery, machine learning & data mining, knowledge management, database management & information systems, information retrieval.

on 29.07.2020 with over 20 presentations by our PhD students on current research topics.