Archive: Stochastik Rhein-Main

Events

Date Category Speakers Title

18.07.2023 Oberseminar Mainz

Andreas Klippel (TU Darmstadt)

Comparison of the random loop model to percolation and infinite loops in the random link model

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07.11.2023 Oberseminar Mainz

Marco Seiler (Goethe-Universität Frankfurt/M.)

Spatial Invasion of Cooperative Parasites

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07.05.2024 Oberseminar Mainz

Prof. Dr. Steffen Dereich (Universität Münster)

New error bounds for the Adam optimisation algorithm

In this talk, I will give an introduction concerning the training of artifcial neural networks based on stochastic gradient descent algorithms. Whereas there are various approaches for carrying out an error analysis for classical stochastic gradient descent, significantly less is known for more elaborate algorithms such as the Adam algorithm. Recently, we established a new approach which allows us to provide error estimates and to reduce this gap. The talk is based on joint work with Arnulf Jentzen. Read more

28.05.2024 Oberseminar Mainz

Stein Andreas Bethuelsen (University of Bergen)

Mixing for Poisson representable processes and the contact process

In this talk I will present some new insights on so-called Poisson representable processes, a general class of {0,1}-valued processes recently introduced by Forsström, Gantert and Steif. Particularly, I will discuss a new characteristic of these in terms of certain mixing properties. As an application thereof, I will argue that the upper invariant measure of the contact process on Z^d is not Poisson representable, thereby answering a question raised in the above mentioned work. This relies on the upper invariant measure satisfying certain directional mixing properties, but not their spatial equivalent. Moreover, the general approach extends to other processes having similar properties, such as the plus phase of the Ising model on Z^2 in the phase transition regime. Read more

04.06.2024 Oberseminar Mainz

Samuel Modee (University of Bergen)

Some rigorous results on the zombie infection model

The so-called zombie infection model is a one-parameter family of interacting particle systems introduced in the physics literature in the 2010’s. This model can be seen as a natural hybrid between a SIR infection model and the bias-voter model. After a brief survey on the basics of this model, we present in this talk some rigorous results, focusing on monotonicity properties and bounds on the probability of a zombie invasion. This is based on joint work, in progress, with Erik Broman and Stein Andreas Bethuelsen. Read more

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