By definition, an $R$-matrix with spectral parameter is a solution to the Yang-Baxter equation, introduced in the 1970's by C.N. Yang and R.J. Baxter. Such a matrix encodes the Boltzmann weights of a lattice model of ...

Statistics for stochastic differential equations (SDEs) attempts to use SDEs as statistical models for real-world phenomena. This involves an understanding of qualitative properties of this class of stochastic processes ...

Homotopical algebra and higher category theory play an increasingly important role in pure mathematics, and higher methods have seen tremendous development in the last couple of decades. The talks delivered at the workshop ...

The first ever MATRIX-MFO tandem workshop addressed several research questions in low-dimensional topology and related areas.

The investigation of Riemannian metrics with lower scalar curvature bounds has been a central topic in differential geometry for decades. It addresses foundational problems, combining ideas and methods from global analysis, ...

This is a report on the Oberwolfach conference "Analysis, geometry and topology of singular PDE'', June 2-12, 2021. This workshop, held in an hybrid format, focused on the topology, geometry and geometric analysis of ...

The recent developments in hyperbolic geometry and flat geometry in real dimension $2$ formed the core of the workshop, with an emphasis on enumerative aspects. A particularly important role in this regard was played by ...

The workshop analyzes the constitution, recovery, and role of the classical texts in mathematical practice throughout history. It aims at problematizing the notion of "classic", to make it a historical category and to study ...

In this virtual workshop a variety of recent developments in Bayesian high-dimensional and nonparametric statistics were discussed in depth. There were 12 in depth talks delivered via zoom in the afternoons (to allow for ...

This hybrid mini-workshop discussed recent mathematical methods for analyzing the opportunities and limitations of data-driven and machine-learning approaches to optimal feedback control. The analysis concerned all aspects ...