Upcoming Events
- Tuesday, 20.10.2026, 15:00 (WIAS-406)
- Seminar Modern Methods in Applied Stochastics and Nonparametric Statistics
Dr. Stefan Schrott, WIAS Berlin:
Adapted transport and Brenier's theorem on spaces of measures
more ... Location
Weierstraß-Institut, Anton-Wilhelm-Amo-Str. 39, 10117 Berlin, 4. Etage, Weierstraß-Hörsaal (Raum: 406)
Further Informations
Dieser Vortrag findet auch via Zoom statt: https://wias-berlin-de.zoom-x.de/j/69982487566
Host
WIAS Berlin
- Wednesday, 21.10.2026, 10:00 (WIAS-ESH)
- Forschungsseminar Mathematische Statistik
Prof. Dr. Kolyan Ray, Imperial College London, GB:
Bayesian regression models with dense confounding variables
more ... Location
Weierstraß-Institut, Anton-Wilhelm-Amo-Str. 39, 10117 Berlin, Erdgeschoss, Erhard-Schmidt-Hörsaal
Abstract
Inferring causal relationships from observational data can be invalidated by the existence of confounding variables. We consider nonparametric Bayesian inference in regression models with additive errors under a dense confounding assumption, i.e. that every confounding variable affects many covariates. We show that by using suitable priors, which are equivalent to marginalizing out the confounders in a certain sense, such confounding can be corrected for. Our approach is illustrated via Gaussian process and spike and slab priors, for which we provide accompanying theoretical guarantees via posterior convergence rates. This is joint work with Luke Travis
Further Informations
Dieser Vortrag findet auch via Zoom statt: https://hu-berlin.zoom-x.de/j/65177102181?pwd=nUMtJOkzDx8xyWzPFezeHh0NEIQUv3.1, Meeting-ID 651 7710 2181, Kenncode: 536200
Host
Humboldt-Universität zu Berlin
Universität Potsdam
WIAS Berlin
- Thursday, 22.10.2026, 10:30 (WIAS-Library)
- Software and Data Seminar
Dr. Laura Prieto Saavedra, WIAS Berlin:
Numerical solution of a Poisson equation using FEniCsx and deal.II
more ... Location
Weierstraß-Institut, Hausvogteiplatz 5-7, 10117 Berlin, R411
Abstract
When developing and studying new numerical methods, it is often useful to have a simple and reliable computational setup for testing ideas, verifying results and comparing discretizations. In this seminar, we will introduce two implementations to solve a Poisson equation numerically using two well-established open-source FEM libraries for solving PDEs: FEniCSx and deal.II. We will go through the math, the basic problem setup, and the essential components of each code, and demonstrate how they can be easily adapted to more difficult problems (e.g., other boundary conditions, other discretizations, etc.). The goal is to provide a simple, reusable starting point that can be modified for different research purposes. No prior FEniCSx or deal.II experience is needed. Basic programming experience is helpful, but not required.
Further Informations
Seminar Software and Data
Host
WIAS Berlin
- Thursday, 22.10.2026, 14:15 (WIAS-ESH)
- Berliner Oberseminar „Nichtlineare partielle Differentialgleichungen” (Langenbach-Seminar)
Clara Thierbach, Humboldt-Universität zu Berlin:
A variational characterization of a Gibbs measure related to the Aviles-Giga functional
more ... Location
Weierstraß-Institut, Anton-Wilhelm-Amo-Str. 39, 10117 Berlin, Erdgeschoss, Erhard-Schmidt-Hörsaal
Host
WIAS Berlin
Humboldt-Universität zu Berlin
Freie Universität Berlin
- Wednesday, 28.10.2026, 10:00 (WIAS-ESH)
- Forschungsseminar Mathematische Statistik
Dr. Nicolas Verzelen, Université Montpellier, Frankreich:
Statistical-computational trade-offs: Low-degree polynomials and community recovery
more ... Location
Weierstraß-Institut, Anton-Wilhelm-Amo-Str. 39, 10117 Berlin, Erdgeschoss, Erhard-Schmidt-Hörsaal
Abstract
In many high-dimensional problems, such as planted clique, sparse PCA, clustering and community detection, the signal strength needed by the best known polynomial-time algorithms is much larger than what is information-theoretically necessary. Is this gap intrinsic? Since NP-hardness says nothing about random instances, evidence of hardness must come from other sources: average-case reductions, or lower bounds for broad classes of algorithms. In the first part, I will introduce the low-degree polynomial framework, starting from testing problems in additive models. In the Gaussian additive model, the χ² divergence and the low-degree advantage admit simple expressions in terms of the overlap between two independent copies of the signal. Comparing them shows how truncating at a low degree discards the rare large overlaps that only exhaustive search can exploit. In the second part, based on joint work with Alexandra Carpentier and Christophe Giraud, I will consider community recovery in the stochastic block model with more than ?n communities. We prove that low-degree polynomials fail below a threshold conjectured by Chin, Mossel, Sohn and Wein, for any graph density, and that this threshold lies below the Kesten?Stigum threshold. We also show that counting suitable motifs succeeds above it in moderately sparse regimes. These motifs are dictated by the lower-bound analysis: cliques, paths, and blow-ups of cycles.
Further Informations
Dieser Vortrag findet auch via Zoom statt: https://hu-berlin.zoom-x.de/j/65177102181?pwd=nUMtJOkzDx8xyWzPFezeHh0NEIQUv3.1, Meeting-ID 651 7710 2181, Kenncode: 536200
Host
Humboldt-Universität zu Berlin
Universität Potsdam
WIAS Berlin
- Wednesday, 28.10.2026, 11:30 (WIAS-406)
- Seminar Interacting Random Systems
Lars Schroeder, University of Twente:
The Geometry of Hierarchical Navigation
more ... Location
Weierstraß-Institut, Anton-Wilhelm-Amo-Str. 39, 10117 Berlin, 4. Etage, Weierstraß-Hörsaal (Raum: 406)
Abstract
Many applications use multi-layered hierarchical data structures for fast approximate nearest-neighbor search in high-dimensional vector spaces. However, the geometric conditions that ensure accurate and efficient greedy navigation remain poorly understood. In this talk, we study the efficiency of greedy navigation on a hierarchy of proximity graphs constructed from n data points on the d-dimensional torus. We identify a deterministic coverage condition under which, given any query q, greedy search returns a point within (1+eps)-factor of the distance to the closest point. This coverage property holds with high probability when the data is distributed as a homogeneous Poisson process, a Hermitian determinantal process, or a bounded-density Cox process, as long as d=o(logn/loglogn). Additionally, we obtain logarithmic expected hop count for the number of greedy hops in fixed dimension. Joint work with Shankar Bhamidi, Souvik Dhara and Clara Stegehuis.
Host
Humboldt-Universität zu Berlin
Technische Universität Berlin
WIAS Berlin
International Research Training Group 2544
- November 3 – 6, 2026 (WIAS-ESH)
- Workshop/Konferenz: Stochastic processes with reinforcement
more ... Location
Weierstraß-Institut, Anton-Wilhelm-Amo-Str. 39, 10117 Berlin, Erdgeschoss, Erhard-Schmidt-Hörsaal
Host
WIAS Berlin
- Wednesday, 04.11.2026, 14:15 (WIAS-405-406)
- Berliner Oberseminar „Nichtlineare partielle Differentialgleichungen” (Langenbach-Seminar)
Prof. Dr. Martin Kružík, Czech Academy of Sciences, Tschechische Republik:
The effects of pressure loads in the dimension reduction of elasticity models
more ... Location
Weierstraß-Institut, Anton-Wilhelm-Amo-Str. 39, 10117 Berlin, 4. Etage, Raum: 405/406
Abstract
We study the dimensional reduction from three to two dimensions in hyperelastic materials subject to a live load, modeled as a constant pressure force. Our results demonstrate that this loading has a significant impact in higher-order scaling regimes, namely those associated with von Kármán-type theories, where a nontrivial interplay arises between the elastic energy and the pressure term. In contrast, we rigorously show that in lower-order bending regimes, as described by Kirchhoff-type theories, the pressure load does not influence the minimizers. Finally, after identifying the corresponding Gamma-limit, we conjecture that a similar independence from the pressure term persists in the most flexible membrane regimes. This is a joint work with F. Riva (Prague).
Further Informations
Oberseminar “Nichtlineare partielle Differentialgleichungen” (Langenbach-Seminar)
Host
Humboldt-Universität zu Berlin
WIAS Berlin
- Wednesday, 18.11.2026, 10:00 (WIAS-ESH)
- Forschungsseminar Mathematische Statistik
Prof. Dr. Botond Szabo, Bocconi University, Italy:
Robust Gaussian process regression: Posterior contraction
more ... Location
Weierstraß-Institut, Anton-Wilhelm-Amo-Str. 39, 10117 Berlin, Erdgeschoss, Erhard-Schmidt-Hörsaal
Abstract
Gaussian processes form a popular and flexible class of prior distributions with principled uncertainty quantification, but the Gaussian likelihood on which they rely makes them highly sensitive to outliers and contaminated observations. We study Gaussian process regression when among the $n$ observations, $m$ of these are possibly contaminated. A generic framework to obtain posterior contraction rates in this setting is considered, from a frequentist perspective as the sample size $n$ and the number of corrupted observations $m$ grow. We adopt a generalised Bayes approach in which the log--likelihood is replaced by a robustified version; we discuss various choices thereof, such as one recently proposed by Altamirano et al. (2024) that preserves conjugacy. We investigate the minimax rate of estimation under adversarial contamination in terms of the Sobolev smoothness $be$ of the regression function and $m$. The question of building adaptive procedures to both $be$ and $m$ is investigated, and we show that a polynomial loss for adaptation must be paid in general. We instantiate our results for Matérn Gaussian process and deep ReLU network priors. Numerical experiments for existing and new robust algorithms are provided, illustrating the practical applicability of our results.
Further Informations
Dieser Vortrag findet auch via Zoom statt: https://hu-berlin.zoom-x.de/j/65177102181?pwd=nUMtJOkzDx8xyWzPFezeHh0NEIQUv3.1, Meeting-ID 651 7710 2181, Kenncode: 536200
Host
Humboldt-Universität zu Berlin
Universität Potsdam
WIAS Berlin
- Wednesday, 18.11.2026, 11:30 (WIAS-406)
- Seminar Interacting Random Systems
Vinicio Rodrigues Moreira, UFMG Brazil:
tba
more ... Location
Weierstraß-Institut, Anton-Wilhelm-Amo-Str. 39, 10117 Berlin, 4. Etage, Weierstraß-Hörsaal (Raum: 406)
Abstract
tba
Further Informations
Seminar Interactin Random Systems
Host
WIAS Berlin
- Wednesday, 18.11.2026, 14:15 (WIAS-ESH)
- Berliner Oberseminar „Nichtlineare partielle Differentialgleichungen” (Langenbach-Seminar)
Gianna Götzmann, Universität Augsburg:
Perturbed minimizing movements of time-dependent functionals on metric spaces
more ... Location
Weierstraß-Institut, Anton-Wilhelm-Amo-Str. 39, 10117 Berlin, Erdgeschoss, Erhard-Schmidt-Hörsaal
Abstract
Minimizing movement schemes are a fundamental tool for approximating evolution equations that have a gradient-flow structure with respect to an energy. Motivated by homogenization problems involving, for instance, geometries that evolve in time, we consider Gamma-converging perturbations of time-dependent driving energies. We study the convergence of the corresponding minimizing movement scheme and provide sufficient conditions under which limits of the scheme are (time-dependent) curves of maximal slope for the limit energy. We further exhibit examples showing that, in general, such a stability property may fail, with the limit motion depending on the relation between the time-discretization parameter τ and the perturbation parameter ϵ. This is joint work with Jan-Frederik Pietschmann and Antonio Tribuzio.
Further Informations
Oberseminar “Nichtlineare partielle Differentialgleichungen” (Langenbach-Seminar)
Host
Humboldt-Universität zu Berlin
WIAS Berlin
- Wednesday, 25.11.2026, 11:30 (WIAS-406)
- Seminar Interacting Random Systems
Ulrik Thinggaard Hansen, Karlsruhe Institute of Technology:
tba
more ... Location
Weierstraß-Institut, Anton-Wilhelm-Amo-Str. 39, 10117 Berlin, 4. Etage, Weierstraß-Hörsaal (Raum: 406)
Abstract
tba
Host
Humboldt-Universität zu Berlin
Technische Universität Berlin
WIAS Berlin
International Research Training Group 2544
- Wednesday, 09.12.2026, 14:15 (WIAS-ESH)
- Berliner Oberseminar „Nichtlineare partielle Differentialgleichungen” (Langenbach-Seminar)
Dr. Kathrin Hellmuth, California Institute of Technology, USA:
Connecting models with data: Inverse problems, their well-posedness and computational techniques
more ... Location
Weierstraß-Institut, Anton-Wilhelm-Amo-Str. 39, 10117 Berlin, Erdgeschoss, Erhard-Schmidt-Hörsaal
Abstract
PDEs model real world systems and build the basis of many downstream applications in optimization, control or uncertainty quantification. To ensure alignment, non-observable model parameters are identified that reconstruct observed data from the real system. The quality of this model fitting procedure depends highly on a-priori knowledge and the quality of data. In this talk we look at how these interact, and present three results in this realm and an outlook on ongoing work. A theoretical study exhibits identifiability of the turning coefficient in a run-and-tumble model for bacterial chemotaxis. Reconstructing this microscopic quantity from experiments that only see the macroscopic bacteria density poses a challenge that we overcome by a delicate construction of an experimental data collection strategy. Second, we propose a new perspective and methodology for experimental design when no such construction is available. Relaxing the search from an optimal to a sufficient design allows us to down-sample experiments according to their sensitivity, an idea borrowed from randomized linear algebra. This keeps the parameter identifiable with high probability. Third, we reconciliate two formulations of gradient-based model fitting for the Fokker?Planck equation, arising from the PDE and particle formulation. Discretization yields gradient estimators that converge at the same rate in the number of particles. We conclude with work in progress on particle-based sampling methods and on uncertainty quantification for equations learned from data.
Further Informations
Oberseminar “Nichtlineare partielle Differentialgleichungen” (Langenbach-Seminar)
Host
Humboldt-Universität zu Berlin
WIAS Berlin
- December 14, 2026 (WIAS-ESH)
- Workshop/Konferenz: CRC/TRR 388 Day on Optimal Transport
more ... Location
Weierstraß-Institut, Anton-Wilhelm-Amo-Str. 39, 10117 Berlin, Erdgeschoss, Erhard-Schmidt-Hörsaal
Host
Technische Universität Berlin
WIAS Berlin