Schedule
Day 1: Monday 27th March 2023
09:00-09:20 Registration
09:20-9:30 Welcome
9:30-11:20 Contributed Session 1
9:30 Talk 1: Alexander Schnurr, Siegen University, Generalized Ordinal Patterns: Definition, Limit Theorems and Applications
9:55 Talk 2: Chiara Amorino, University of Luxemburg, Parameter estimation of discretely observed interacting particle systems
10:20 Talk 3: Henrik Valett, Christian-Albrechts-Universität zu Kiel, Parameter estimation for polynomial processes
10:55 Talk 4: Martin Bladt, University of Copenhagen, Conditional Aalen-Johansen estimator
11:20-11:50 Coffee break
11:50-13:05 Contributed Session 2
11:50 Talk 5: Matthias Vetter, Kiel University, Jump regressions revisited
12:15 Talk 6: Maximilian Steffen, Karlsruhe Institute of Technology (KIT), Estimating a multivariate Levy density based on discrete observations
12:40 Talk 7: Markus Bibinger, Julius-Maximilians-Universität Würzburg, Testing for jumps in processes with integral fractional part and jump-robust inference on the Hurst exponent
13:05 - 14:00 Lunch
14:00-15:20 Contributed Session 3
14:00 Talk 8: Johannes Brutsche, University of Freiburg, Sharp adaptive similarity testing with pathwise stability for ergodic diffusions
14:25 Talk 9: Yury Kutoyants, Le Mans University, Hidden Markov Processes and Adaptive Filtration. Ergodic Case.
14:55 Talk 10: Nicolas Lengert, University of Luxemburg, Estimation of quadratic covariation of an asynchronously observed bivariate beta- stable process
15:20-15:50 Coffee break
15:50-17:05 Contributed Session 4
15:50 Talk 11: Elise Bayraktar, Université Gustave Eiffel, Estimation of pure-jump stable Cox-Ingersoll-Ross processes from high-frequency observations
16:15 Talk 12: Riccardo Passeggeri, Imperial College London, A Universal robustification procedure
16:40 Talk 13: Yuan Li, Imperial College London, A GMM approach for estimation of Brownian semistationary processes
Day 2: Tuesday 28th March 2023
9:30-11:20 Contributed Session 5:
9:30 Talk 14: Jonas Hermansen, University of Copenhagen, Stochastic Differential Equations with Random Effects: Existence and Uniqueness of Solutions
9:55 Talk 15: Gregor Pasemann, Humboldt-Universität zu Berlin, Parameter Estimation from Noisy Observations of a Stochastic Heat Equation
10:20 Talk 16: Sebastian Ertel, TU Berlin, Ensemble Kalman-Bucy filters for finite and infinite dimensional signals
10:55 Talk 17: Marc Corstanje, Vrije Universiteit Amsterdam, Likelihood-based inference for partially observed chemical reaction processes
11:20-11:50 Coffee break
11:50-13:05 Contributed Session 6
11:50 Talk 18: Nakahiro Yoshida, University of Tokyo, Batched bandits and conditional Edgeworth expansion
12:15 Talk 19: Sascha Gaudlitz, Humboldt University Berlin, Finite-time non-parametric inference on the reaction term in 1d semi-linear SPDEs
12:40 Talk 20: Dion-Blanc, LPSM, Sorbonne Université, Multiclass classification for Hawkes processes
13:05 - 14:00 Lunch
14:00-15:20 Contributed Session 7
14:00 Talk 21: Masayuki Uchida, Osaka University, Estimation for a discretely observed linear parabolic SPDE in two space dimensions with a small noise
14:25 Talk 22: Josef Janak, Karlsruhe Institute of Technology, Estimation of the diffusivity parameter in the stochastic heat equation with multiplicative noise
14:55 Talk 23: Shogo Nakakita, University of Tokyo, Parametric estimation of ergodic diffusion processes by online gradient descent
15:20-15:50 Coffee break
15:50-17:05 Contributed Session 8
15:50 Talk 24: Kolyan Ray, Imperial College London, Bayesian estimation in a multidimensional diffusion model with high frequency data
16:15 Talk 25: Thorben Pieper, TU Delft, Bayesian Computation for Discretely Observed Stochastic Partial Differential Equations
16:40 Talk 26: Peter Spreij, University of Amsterdam, Nonparametric Bayesian volatility estimation for gamma-driven stochastic differential equations
17:05-17:10 Break
17:10-17:40 Dynstoch Network Meeting (All welcome)
18:30 Workshop dinner (Registration required)
Day 3: Wednesday 29th March 2023
9:25-10:55 Contributed Session 9 (STUOD)
9:25 Dan Crisan: Brief overview of the STUOD project
9:30 Talk 27: Oana Lang, Imperial College London, On global solutions for a class of SPDEs which originate in fluid dynamics
9:55 Talk 28: Bertrand Chapron, Ifremer, Markovian and non-Markovian closure for wave-turbulence interaction
10:20 Talk 29: Valentin Resseguir, Lab, Scalian DS, Rennes, Estimation of multiplicative noise operator statistics for reduced data assimilation in fluid mechanics
10:55-11:25 Coffee break
11:25-12:40 Contributed Session 10 (STUOD cont’d)
11:25 Talk 30: Said Ouala, IMT Atlantique, Lab-STICC, Brest, On the derivation of data-driven models for partially observed systems
11:50 Talk 31: Alexander Lobbe, Imperial College London, Noise calibration for the stochastic rotating shallow water model
12:15 Talk 32: Salvador Ortiz-Latorre, University of Oslo, SPDE bridges with observation noise and their spatial approximation
12:40 – 13:40 Lunch
13:40-15:25 Contributed Session 11
13:40 Talk 33: Yuga Iguchi, UCL, Parameter Estimation with Increased Precision for Elliptic and Hypo-elliptic Diffusions
14:05 Talk 34: Lorenzo Lucchese, Imperial College London, Estimation and Inference for Multivariate Continuous-Time AutoRegressive (MCAR) Processes
14:30 Talk 35: Dan Leonte, Imperial College London, Parameter inference and forecasting for trawl processes and simple ambit fields
14:55-15:25 Coffee break & Vote for best presentation given by PhD students
15:25-16:40 Contributed Session 12
15:25 Talk 36: Sami Umut Can, University of Amsterdam, Goodness-of-Fit Testing for Point Processes in Survival Analysis
15:50 Talk 37: Alessandra Luati, Imperial College London, On the optimality of score-driven models
16:15 Talk 38: Frank van der Meulen, Vrije Universiteit Amsterdam, Compositionality in filtering
16:45 Award of book prizes kindly donated by WSPC for the six best presentations by PhD students