Archiv: Stochastik Rhein-Main

25.01.2018 Oberseminar Darmstadt

Mikhail Lifshits ((St. Petersburg))

A hierarchical renormalisation model

29.06.2022 Andere Veranstaltungen

Naomi Feldheim (Bar-Ilan University, Israel)

Zeroes of Gaussian stationary Functions

12.02.2021 Rhein-Main-Kolloquium

Rongfeng Sun (NUS, Singapore)
Nikos Zygouras (Warwick)

RMK Mainz - ONLINE

03.12.2021 Rhein-Main-Kolloquium

Nina Gantert (Technische Universität München)
Paolo Dai Pra (Università degli Studi di Verona)

RMK Frankfurt - ONLINE EVENT

04.11.2025 Oberseminar Mainz

Noela Müller (Universität Eindhoven)

ENTFÄLLT LEIDER KURZFRISTIG !!!

07.11.2024 Oberseminar Darmstadt

Noemi Kurt (Goethe-Universität Frankfurt)

Dormancy in population genetics and interacting particle systems

19.01.2018 Rhein-Main-Kolloquium

Peter Mörters (Universität Köln)
Steffen Dereich (Universität Münster)

tba

18.11.2019 Stochastik-Kolloquium Frankfurt

Prof. Dr. Dirk Metzler (FB Biologie/ LMU München)

Hybridzone zwischen Rabenkrähen und Nebelkrähen: Artbildung allein durch Paarungspräferenzen?

10.05.2017 Stochastik-Kolloquium Frankfurt

Prof. Dr. Hsien-Kuei Hwang (Academia Sinica, Taipeh)

Coin-tossing in Algorithmics

30.10.2019 Stochastik-Kolloquium Frankfurt

Prof. Dr. Hsien-Kuei Hwang (Academia Sinica, Taipeh)

Stirling numbers of the second kind: the history of early developments and an elementary approach to asymptotic normality

08.11.2017 Stochastik-Kolloquium Frankfurt

Prof. Dr. Sebastian Doehler (Hochschule Darmstadt)

New false discovery rate controlling procedures for discrete data

12.06.2018 Stochastik-Kolloquium Frankfurt

Prof. Dr. Sebastian Mentemeier

Limit theorems for recursive cell-splitting schemes

07.02.2023 Oberseminar Mainz

Prof. Dr. Steffen Dereich (Universität Münster)

Oberseminar Stochastik Mainz - 07.05.2024 - Prof. Dr. Steffen Dereich (WWU Münster)

Titel: New error bounds for the Adam optimisation algorithm Abstract: In this talk, I will give an introduction concerning the training of artificial 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. weiterlesen

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. weiterlesen

16.05.2017 Stochastik-Kolloquium Frankfurt

Prof. Dr. Sylvie Roelly (Universität Potsdam)

Die Renaissance des Werkes des Mathematikers Vincent Doeblin

23.06.2022 Oberseminar Darmstadt

Quirin Vogel (NYU Shanghai)

The limit of the Feynman representation for the Bose gas

25.04.2024 Oberseminar Darmstadt

Ralph Neininger (Goethe-Universität Frankfurt)

Recursive distributional equations in applications

09.07.2026 Oberseminar Darmstadt

Rebecca Steiner (JGU Mainz)

Multi-drawing Pólya urns via labelled random DAGs

26.11.2024 Oberseminar Mainz

Reinhard Höpfner (Johannes Gutenberg-Universität JGU Mainz)

Circuits von Hodgkin-Huxley-Neuronen

15.04.2025 Oberseminar Mainz

Réka Szabó (University of Groningen)

Oberseminar Mainz

How single cell properties can change network synchronization: The saddle-node loop bifurcation in neuron models - Neurons have traditionally been classified into two types depending on their frequency-input curve. Both types are associated with a particular dynamic transition from rest to spiking. Our work highlights a third transition, for which we found experimental evidence in hippocampal slices. For typical Hodgkin-Huxley-like neuron model, we present a universal bifurcation structure, with the separation of timescale between voltage and ion channel dynamics as one of the bifurcation parameters. We predict that the strongest changes in synchronization with small parameter changes occur at a particular co-dimension two bifurcation, the saddle-node loop bifurcation, and we present characteristics of this transition, from changes in firing rate to phase response curve and synchronization. We will conclude with a short overview over our current research on stress resilience. weiterlesen

Veranstaltungsarchiv

Events

A hierarchical renormalisation model

Zeroes of Gaussian stationary Functions

RMK Mainz - ONLINE

RMK Frankfurt - ONLINE EVENT

ENTFÄLLT LEIDER KURZFRISTIG !!!

Dormancy in population genetics and interacting particle systems

tba

Hybridzone zwischen Rabenkrähen und Nebelkrähen: Artbildung allein durch Paarungspräferenzen?

Coin-tossing in Algorithmics

Stirling numbers of the second kind: the history of early developments and an elementary approach to asymptotic normality

New false discovery rate controlling procedures for discrete data

Limit theorems for recursive cell-splitting schemes

Oberseminar Stochastik Mainz - 07.05.2024 - Prof. Dr. Steffen Dereich (WWU Münster)

New error bounds for the Adam optimisation algorithm

Die Renaissance des Werkes des Mathematikers Vincent Doeblin

The limit of the Feynman representation for the Bose gas

Recursive distributional equations in applications

Multi-drawing Pólya urns via labelled random DAGs

Circuits von Hodgkin-Huxley-Neuronen

Oberseminar Mainz

Überblick

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