Upcoming Events

Many events are currently organized online. Information on how to access these events can be found by clicking “more” below the respective entry.


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Monday, 05.12.2022, 10:30 (WIAS-406)
Seminar in Machine Learning and Data-Driven Optimization
Yucen Luo, Max Planck Institute for Intelligent Systems:
Spectral representation learning for conditional moment models (hybrid talk)
more ... Location
Weierstraß-Institut, Mohrenstr. 39, 10117 Berlin, 4. Etage, Weierstraß-Hörsaal (Raum: 406)

Abstract
Many problems in causal inference and economics can be formulated in the framework of conditional moment models, which characterize the target function through a collection of conditional moment restrictions. For nonparametric conditional moment models, efficient estimation has always relied on preimposed conditions on various measures of ill-posedness of the hypothesis space, which are hard to validate when flexible models are used. In this work, we address this issue by proposing a procedure that automatically learns representations with controlled measures of ill-posedness. Our method approximates a linear representation defined by the spectral decomposition of a conditional expectation operator, which can be used for kernelized estimators and is known to facilitate minimax optimal estimation in certain settings. We show this representation can be efficiently estimated from data, and establish $L_2$ consistency for the resulting estimator. We evaluate the proposed method on proximal causal inference tasks, exhibiting promising performance on high-dimensional, semi-synthetic data.

Further Informations
The talk is also given via Zoom: https://us02web.zoom.us/j/8994552597

Host
WIAS Berlin
Tuesday, 06.12.2022, 15:00 (WIAS-405-406)
Seminar Modern Methods in Applied Stochastics and Nonparametric Statistics
Dr. Alexandra Suvorikova, WIAS Berlin:
Anomaly detection in biometric authentication (hybrid talk)
more ... Location
Weierstraß-Institut, Mohrenstr. 39, 10117 Berlin, 4. Etage, Raum: 405/406

Abstract
In this work we suggest a novel framework to detect user behaviour anomalies based on transfer learning approach combined with optimal transport techniques.

Further Informations
Dieser Vortrag findet bei Zoom statt: https://zoom.us/j/492088715

Host
WIAS Berlin
Wednesday, 07.12.2022, 10:00 (WIAS-ESH)
Forschungsseminar Mathematische Statistik
Prof. Mathias Vetter, Christian-Albrechts-Universität zu Kiel:
On goodness-of-fit testing for point processes (hybrid talk)
more ... Location
Weierstraß-Institut, Mohrenstr. 39, 10117 Berlin, Erdgeschoss, Erhard-Schmidt-Hörsaal

Abstract
Typical models for point processes like Hawkes processes or inhomogeneous Poisson processes are often of a parametric form where the intensity function or an additional self-exciting component is known up to an unspecified parameter. A lot of research since the seminal paper by Ogata (1978) has been devoted to the estimation of these unknown parameters but even in these rather standard models a consistent goodness-of-fit test has been missing. This talk aims to fill this gap. We will show how to formally set up a bootstrap procedure to allow for goodness-of-fit testing and we will discuss how to prove consistency of the test in the (already quite involved) case of an inhomogenous Poisson process.

Further Informations
Der Vortrag findet bei Zoom statt: https://zoom.us/j/159082384

Host
Humboldt-Universität zu Berlin
Universität Potsdam
WIAS Berlin
Wednesday, 07.12.2022, 11:30 (WIAS-405-406)
Seminar Interacting Random Systems
Daniel Heydecker, MPI Leipzig:
From LDPs of the Kac Process to the H-Theorem
more ... Location
Weierstraß-Institut, Mohrenstr. 39, 10117 Berlin, 4. Etage, Raum: 405/406

Abstract
It is well-recognised that the large deviations of particle systems are connected to the appearance of a gradient flow formulation through a reformulation of the dynamical large deviations cost. In this talk, I will discuss a simple proof of Boltzmann's H-Theorem in the spatially homogeneous Boltzmann equation, which yields the equality between entropy and integrated entropy dissipation under quite general conditions. Time allowing, I will also discuss recent work applying the same principles to the porous medium equation.

Further Informations
Seminar Interacting Random Systems

Host
WIAS Berlin
Tuesday, 13.12.2022, 15:00 (WIAS-405-406)
Seminar Modern Methods in Applied Stochastics and Nonparametric Statistics
Dr. Amal Alphonse, WIAS Berlin:
Risk-averse optimal control of random elliptic variational inequalities (hybrid talk)
more ... Location
Weierstraß-Institut, Mohrenstr. 39, 10117 Berlin, 4. Etage, Raum: 405/406

Abstract
In this talk, I will discuss a risk-averse optimal control problem governed by an elliptic variational inequality (VI) subject to random inputs. I will derive two forms of first-order stationarity conditions for the problem by passing to the limit in a penalised and smoothed approximating control problem. The lack of regularity with respect to the uncertain parameters and complexities induced by the presence of the risk measure give rise to delicate analytical challenges seemingly unique to the stochastic setting. To finish, I will briefly discuss a path-following stochastic approximation algorithm and demonstrate it on an example.

Further Informations
Dieser Vortrag findet bei Zoom statt: https://zoom.us/j/492088715

Host
WIAS Berlin
Wednesday, 14.12.2022, 10:00 (WIAS-ESH)
Forschungsseminar Mathematische Statistik
Jovanka Lili Matic, Humboldt-Universität zu Berlin:
Global sensitivity analysis in the presence of missing values (hybrid talk)
more ... Location
Weierstraß-Institut, Mohrenstr. 39, 10117 Berlin, Erdgeschoss, Erhard-Schmidt-Hörsaal

Further Informations
Der Vortrag findet bei Zoom statt: https://zoom.us/j/159082384

Host
Humboldt-Universität zu Berlin
Universität Potsdam
WIAS Berlin
Wednesday, 14.12.2022, 10:30 (WIAS-Library)
Seminar in Machine Learning and Data-Driven Optimization
Heiner Kremer/Yassine Nammour, Max Planck Institute for Intelligent Systems:
Distributionally robust machine learning via conditional moment restrictions (hybrid talk)
more ... Location
Weierstraß-Institut, Hausvogteiplatz 5-7, 10117 Berlin, R411

Further Informations
The talk is also given via Zoom: https://us02web.zoom.us/j/8994552597

Host
WIAS Berlin
Wednesday, 14.12.2022, 11:30 (WIAS-405-406)
Seminar Interacting Random Systems
Andreas Klippel, TU Darmstadt:
tba
more ... Location
Weierstraß-Institut, Mohrenstr. 39, 10117 Berlin, 4. Etage, Raum: 405/406

Further Informations
Seminar Interacting Random Systems

Host
WIAS Berlin
Wednesday, 14.12.2022, 15:15 (WIAS-ESH)
Berliner Oberseminar „Nichtlineare partielle Differentialgleichungen” (Langenbach-Seminar)
Dr. Katharina Hopf, WIAS Berlin:
The Cauchy problem for a cross-diffusion system with incomplete diffusion (hybrid talk)
more ... Location
Weierstraß-Institut, Mohrenstr. 39, 10117 Berlin, Erdgeschoss, Erhard-Schmidt-Hörsaal

Further Informations
Hybridveranstaltung - Teilnahme vor Ort bitte bei Dr. A. Glitzky (annegret.glitzky@wias-berlin.de) anmelden.
Hybrid event - please give Dr. A. Glitzky (annegret.glitzky@wias-berlin.de) notice of your on-site participation.

Host
Humboldt-Universität zu Berlin
WIAS Berlin
Friday, 16.12.2022, 13:00 (WIAS-Library)
E-Coffee-Lecture
Dr. Eleanor Eife-Horn, WIAS:
Introduction to the MyProTime absence management system and updates on the federal travel expenses act
more ... Location
Weierstraß-Institut, Hausvogteiplatz 5-7, 10117 Berlin, R411

Further Informations
Online (hybrid) event

Host
WIAS Berlin
Tuesday, 10.01.2023, 15:00 (WIAS-405-406)
Seminar Modern Methods in Applied Stochastics and Nonparametric Statistics
Robert Gruhlke, WIAS Berlin:
Wasserstein polynomial chaos and Langevin dynamics (hybrid talk)
more ... Location
Weierstraß-Institut, Mohrenstr. 39, 10117 Berlin, 4. Etage, Raum: 405/406

Abstract
An unsupervised learning approach for the computation of an explicit functional representation of a random vector is presented, which only relies on a finite set of samples from an unknown distribution. Motivated by recent advances with computational optimal transport for estimating Wasserstein distances, we develop a generative model denoted as Wasserstein multi-element polynomial chaos expansion (WPCE). It relies on the minimization of a regularized empirical Wasserstein metric known as debiased Sinkhorn divergence. Since the used PCE grows exponentially in the number of underlying input random coordinates, we introduce an appropriate low-rank format given as stacks of tensor trains. This alleviates the curse of dimensionality, leading to only linear dependence on the input dimension. Ensemble methods nowadays are ubiquitous for the solution of Bayesian inference problems. We discuss recent advances based on state-of-the-art samplers such as Affine Invariant Langevin Dynamics (ALDI) that allow for increased convergence speed and in turn reduce the required number of forward calls encoded in the drift term of the underlying stochastic differential equation. This improvement is realised through possible adaptive ensemble enrichment and an adapted Langevin dynamics based on a homotopy formalism. Optionally, the history of particles obtained within the solution process of the Langevin dynamics then can be used to numerically construct a push forward map in terms of WPCE. Once computed, this provides functional access to the posterior without the need of further forward model evaluations.

Further Informations
Dieser Vortrag findet bei Zoom statt: https://zoom.us/j/492088715

Host
WIAS Berlin
Wednesday, 08.02.2023, 15:15 (WIAS-ESH)
Berliner Oberseminar „Nichtlineare partielle Differentialgleichungen” (Langenbach-Seminar)
Jun. Prof. Dr. Patrick Tolksdorf, Johannes Gutenberg-Universität Mainz:
On off-diagonal behavior of the generalized Stokes operator (hybrid talk)
more ... Location
Weierstraß-Institut, Mohrenstr. 39, 10117 Berlin, Erdgeschoss, Erhard-Schmidt-Hörsaal

Further Informations
Hybridveranstaltung - Teilnahme vor Ort bitte bei Dr. A. Glitzky (annegret.glitzky@wias-berlin.de) anmelden.
Hybrid event - please give Dr. A. Glitzky (annegret.glitzky@wias-berlin.de) notice of your on-site participation.

Host
Humboldt-Universität zu Berlin
WIAS Berlin