The Foundations of Data Science and Machine Learning workshop (FoCM 2026) focuses on algorithms that enable computers to learn based on data, with particular emphasis on recognizing complex patterns and making intelligent, data-driven decisions. Closely tied to statistics, probability theory, data mining, pattern recognition, artificial intelligence, adaptiv…
This talk considers the numerical solution of high-frequency scattering problems modelled by the Helmholtz equation with a bounded obstacle. Although the analysis of this problem d…
The Adapted Wasserstein distance has been proven to be a suitable metric for comparing stochastic processes while accounting for the evolution of information in time, especially fo…
A basic problem in Enumerative Combinatorics is to count the number of objects with fixed size in a class of objects, as for instance, to enumerate the number of plane trees of siz…
What structural graph properties are useful in designing efficient algorithms? Tree decompositions have been successfully used for this purpose, provided that the decomposition is …
Vasil A. Popov Prize
Generative flows, in particular flow matching provides state-of-the-art performance for sampling from (conditional) continuous distributions. The talk gives a brief introduction in…
Szanto Medal
Two-dimensional (2-D) fluids produce fascinating patterns of swirling motion. How and why the patterns emerge are long-standing questions, first addressed in the 19th century. Coun…
What does it mean when 27 companies show up — and 1 bet on three roles at once?
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The Triple-Threat
Of 62 on the bill · classified by free-text title