Million funding for Deep Learning project in Leipzig

Mathematical models and methods and computing with neural networks form the theoretical foundations for the study of deep learning processes. © Max Planck Institute for Mathematics in the Sciences

Deep Learning is one of the most vibrant areas of contemporary machine learning and one of the most promising approaches to Artificial Intelligence. This research area drives the latest systems for image, text, and audio processing, as well as an increasing number of new technologies. The goal of this new research group is to advance on key open problems in Deep Learning, specifically those regarding the capacity, optimisation, and regularisation of the underlying algorithms.

The scientists will consolidate a theoretical basis that allows to pin down the inner workings of the present success of Deep Learning and make it more widely applicable, in particular in situations with limited data and challenging problems in reinforcement learning. The scientific approach is based on the geometry of neural networks and exploits innovative mathematics, drawing on information geometry and algebraic statistics.

Guido Montúfar studied mathematics and physics at the Technical University of Berlin and received his doctorate at the University of Leipzig. After working as a research associate at the Pennsylvania State University, he obtained a postdoc position at the Max Planck Institute for Mathematics in the Sciences.

In parallel to his recent position as research group leader he holds an Assistant Professorship at the Departments of Mathematics and Statistics at the University of California, Los Angeles, USA. With his team at UCLA, he develops mathematical tools and techniques for computation with neural networks, with diverse applications from generative modelling, optimisation, to pure mathematics.

Guido Montúfar’s work is dedicated to advancing on the most important challenges in deep learning today, with deep and direct practical relevance. Together with his team, he pursues a synergistic approach at the intersection of Mathematics, Statistics, Machine learning, merging tools from information theory, algebra, combinatorics, and geometry.

The geometric analysis of deep neural networks that Guido has been developing over the past years provides a formal approach to the design of learning systems that allows, for instance, to create sparse networks with guaranteed learning capabilities. His work on neural networks includes the analysis of distributed representations, the advantages of depth in function approximation, the geometry of graphical models with hidden variables.

This work is opening up new avenues for addressing one of the most serious bottlenecks in contemporary reinforcement learning, namely the sample complexity of these methods. This work is also facilitating the development of new optimization algorithms for learning with neural networks and new regularization techniques based on information theory.

Guido is also an active coordinator of research activities targeting interactions between mathematics and machine learning, such as the recent DALI workshop on “Theory of Deep Learning” and the upcoming AIM workshop “Boltzmann Machines” at the American Institute of Mathematics. Guido Montúfar’s team is also closely involved in the Mathematics of Data initiative at the Max Planck Institute for Mathematics in the Sciences.

ERC Starting Grants are awarded by the European Research Council to excellent junior researchers who have already achieved outstanding research results. The funding is used to set up an own working group.

Dr. Guido Montúfar
Max Planck Institute for Mathematics in the Sciences
Inselstraße 22
04103 Leipzig
Germany Information about the laureate Dr. Guido Montúfar: Information about the ERC Starting Grants Program Information about the „Mathematics of Data“-Initiative at the Max Planck Institute for Mathematics in the Sciences Information about the Max Planck Institute for Mathematics in the Sciences

Media Contact

Jana Gregor Max-Planck-Institut für Mathematik in den Naturwissenschaften (MPIMIS)

All news from this category: Awards Funding

Back to the Homepage

Comments (0)

Write comment

Latest posts

Seawater as an electrical cable !?

Wireless power transfers in the ocean For drones that can be stationed underwater for the adoption of ICT in mariculture. Associate professor Masaya Tamura, Kousuke Murai (who has completed the…

Rare quadruple-helix DNA found in living human cells with glowing probes

New probes allow scientists to see four-stranded DNA interacting with molecules inside living human cells, unravelling its role in cellular processes. DNA usually forms the classic double helix shape of…

A rift in the retina may help repair the optic nerve

In experiments in mouse tissues and human cells, Johns Hopkins Medicine researchers say they have found that removing a membrane that lines the back of the eye may improve the…

Partners & Sponsors

By continuing to use the site, you agree to the use of cookies. more information

The cookie settings on this website are set to "allow cookies" to give you the best browsing experience possible. If you continue to use this website without changing your cookie settings or you click "Accept" below then you are consenting to this.