Events

This workshop brings together researchers from three distinct streams of mathematics: the classical rigidity theory of bar-joint and tensegrity frameworks in combinatorics and discrete geometry; the theory of generalized circle packing that arose from the study of 3-manifolds in geometric topology, extending to sphere packing and jamming; and discrete differential geometry. A scattering of results in recent years has started to forge connections among these fields. The main aim of the workshop is to encourage their cross-fertilization, with particular emphasis on the rigidity of inversive distance packings. Participants will attend presentations on cutting-edge research and initiate new collaborations.

The Institute for Mathematical Stochastics at the Technical University Braunschweig will host the Workshop "Stochastic processes on random geometries” scheduled from February 17-21 2025. The program will feature two mini lecture series delivered by: Martin Barlow (University of British Columbia) Nina Gantert (TU Munich) In addition, the event will include 14 invited lectures and one session dedicated to young researchers. The specific topics include random walks in random environment, static and dynamic percolation, interacting particle systems, statistical mechanics and their applications in physics, materials science and biology. Our aim is to provide a platform for the presentation of recent results, national and international scientific exchange and the education of younger scientists that are interested in the subject. For more information, including a list of invited speakers and a link for registration, see the workshop webpage. The workshop is supported by the SSP2265 "Random Geometric Systems".

Researchers working on graph algorithms use a broad range of different criteria for deciding what makes an algorithm efficient. While in theory the dominant benchmark is the asymptotic running time, in practice the story is more nuanced: an algorithm needs to be simple enough to be implementable, fast on graphs of bounded size, space efficient, cache-friendly, and easy to test. While many of these requirements motivate interesting algorithmic questions that are highly relevant in practice, they are often overlooked by the theory community. The goal of the workshop is to foster the exchange of ideas between researchers working on graph algorithms, which have high practical relevance. The workshop will include overview talks on the various perspectives, research talks, an open problem session, and structured time for collaboration. The topics of the workshop include fundamental data science graph algorithms (e.g., clustering, partitioning, graph embedding), graph neural networks, and modeling data using networks (e.g. approximate nearest neighbor search). Additionally, the workshop program incorporates problems and approaches necessitated by scaling graph algorithms to large datasets (e.g. parallel, distributed, dynamic and external memory models, as well as algorithm engineering).

The school in Geilo will be devoted to selected topics in analysis, geometry, and differential equations. Participants are invited to stay from Sunday evening March 2 to Friday March 7. The scientific program for the winter school will begin in the morning of Monday March 3. The main lecturers are: -Sean Curry (Oklahoma, USA) The Geometry of Strongly Pseudoconvex Domains -Sigmund Selberg (Bergen, Norway) TBA -Francisco Torres de Lizaur (Seville, Spain) TBA -Enrico Le Donne (Fribourg, Switzerland) (to be confirmed) In addition to these, the meeting will have regular / contributed lectures by participants.

Control theory and reinforcement learning converge on a shared objective: facilitating autonomous, real-time decision-making to optimize dynamical processes. Historically, these disciplines have diverged in assumptions regarding available prior information and in analytical techniques applied. However, recent advances bridging the two domains are fostering collaborations. The upcoming CWI research semester programme in spring 2025, themed "Control Theory and Reinforcement Learning: Connections and Challenges", will comprise a spring school and workshops on various sub-topics, orchestrated by a distinguished team including Aditya Gilra, Bert Kappen, Debabrota Basu, Frans Oliehoek, Maryam Kamgarpour and Sean Meyn, to explore the intersections and challenges within these intertwined fields.

This workshop will be centered on recent advances in graph rigidity and interactions between rigidity, algebraic statistics, and matroid theory. Three major advances are the recent resolution of the matroid maximality conjecture, the newly developed link to maximum likelihood estimation in Gaussian graphical models, and the recent positive resolution of Lovasz and Yemini's connectivity conjecture for generic rigidity. The workshop will showcase a diverse sample of current work addressing fundamental problems in graph rigidity, algebraic matroids, and algebraic statistics.

This is an informal workshop entirely dedicated to young mathematicians who work in differential geometry in a broad sense. The scientific theme of the workshop is the study of topological and geometric properties of complex manifolds, and, more in general, of manifolds endowed with ''special'' geometric structures, either integrable or non-integrable.