Scientific organisers
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Jonas Latz, Heriot-Watt University
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Eric Moulines, Ecole Polytechnique
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Andrew Stuart , California Institute of Technology
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Aretha Teckentrup , University of Edinburgh
About:
This workshop was part of the Isaac Newton Institute programme on The mathematical and statistical foundation of future data-driven engineering:
https://www.newton.ac.uk/event/dde/
In tandem with the workshop on Computational Challenges and Emerging Tools, this week-long workshop focused on algorithms and methodology to address key tasks in data-driven engineering, including:
- data assimilation and statistical inverse problems,
- reinforcement learning and control,
- model order reduction,
- bridging mechanistic and data-driven models and methods.
A particular focus of this workshop was on the underlying mathematical and statistical foundations required to make computational tools efficient and transferable.
Programme:
| Tuesday 9 May 2023 | |
| Registration and refreshments | |
| Welcome and housekeeping (organisers and ICMS) | |
| Susana Gomes, University of Warwick | Parameter Estimation for Macroscopic Pedestrian Dynamics Models using Microscopic Data |
| Sebastian Reich, University of Potsdam | Minimum variance estimation for continuous time data assimilation |
| Lunch break | |
| Michela Ottobre, Heriot-Watt University | On Multiscale dynamics |
| Dan Crisan, Imperial College London | Data assimilation for a Quasi-Geostrophic Model with Circulation-Preserving Stochastic Transport Noise |
| Coffee break | |
| Mateusz Majka, Heriot-Watt University | Solving mean-field games via fictitious play and birth-death |
| Hanne Kekkonen, Delft University of Technology | Public lecture: Mathematics of Images |
| Drinks reception at ICMS | |
| Wednesday 10 May 2023 | |
| Richard Nickl, University of Cambridge | On the computational complexity of MCMC in non-linear high-dimensional regression models |
| Margaret Trautner, Caltech | Operator Learning for Multiscale PDEs in Solid Mechanics |
| Coffee break | |
| Daniel Walter, Humboldt-Universität zu Berlin | A closed loop learning approach for optimal feedback laws in nonlinear control problems |
| Group photo and lunch | |
| Workshop dinner | |
| Thursday 11 May 2023 | |
| Alexandros Beskos, UCL | Manifold Markov chain Monte Carlo methods for Bayesian inference in diffusion models |
| Kostas Zygalakis , University of Edinburgh | On the connections between sampling, optimization and (stochastic) differential equations |
| Coffee break | |
| Sinho Chewi, Massachusetts Institute of Technology | Faster high-accuracy log-concave sampling via algorithmic warm starts |
| Lunch break | |
| Björn Sprungk, TU Bergakademie Freiberg | Noise-level robust Markov chain Monte Carlo and pushforward Markov kernels |
| François-Xavier Briol, UCL | Multilevel Bayesian quadrature |
| Coffee break | |
| Jana de Wiljes, University of Potsdam | Sequential Bayesian Learning |
| Poster session and drinks reception | |
| Friday 12 May 2023 | |
| Tim Sullivan, University of Warwick | Recent advances in the definition and stability of non-parametric MAP estimators |
| Robert Scheichl, Heidelberg University | Surrogates Based on Low-Rank Tensor Approximation for Future Data-Driven Engineering |
| Coffee break | |
| Karen Veroy-Grepl, Eindhoven University of Technology | Model Order Reduction in Data Assimilation |
| Closing remarks | |
| Take away lunch and end of workshop |
