Program


Tuesday, June 7, 2022


08:00 - 08:30 Welcome of participants - Registration  
08:30 - 08:45 Opening speech (Jean-Marc Bourinet, Rodolphe Le Riche)  
08:45 - 09:30 Inv talk #1 - Sparse neural networks for forward and inverse estimation (Bojana Rosic) (Chairs: Victor Picheny, Céline Helbert)     
09:30 - 10:30 PhD student talks #1-2 (Chairs: Sonja Kuhnt, Olivier Zahm)  
    09:30 - 10:00 PhD talk #1 - Robust prediction interval estimation for Gaussian processes by cross-validation method (Naoufal Acharki)      
    10:00 - 10:30 PhD talk #2 - Multi-fidelity surrogate modelling for time-series output (Baptiste Kerleguer)     
10:30 - 11:00 Coffee break  
11:00 - 12:30 PhD student talks #3-5 (chairs: Sébastien Da Veiga, Carsten Proppe)  
    11:00 - 11:30 PhD talk #3 - Randomized maximum likelihood via high-dimensional Bayesian optimization (Valentin Breaz)     
    11:30 - 12:00 PhD talk #4 - Leveraging spatial regularity in distribution field estimation to accelerate statistical inference for the sciences (Athénaïs Gautier)     
    12:00 - 12:30 PhD talk #5 - Universal inversion: extending universal kriging to include trends in Bayesian inverse problems (Cédric Travelletti)     
12:30 - 14:00 Lunch  
14:00 - 15:30 PhD student talks #6-8 (Chairs: Daniel Straub, Maria Joan Rendas)  
    14:00 - 14:30 PhD talk #6 - When global sensitivity analysis provides insight into group fairness (Clément Bénesse)     
    14:30 - 15:00 PhD talk #7 - Relaxed Gaussian process interpolation: a goal-oriented approach to Bayesian optimization (Sébastien Petit)     
    15:00 - 15:30 PhD talk #8 - Dynamical low rank approximation in molecular dynamics and optimal control (David Sommer)     
15:30 - 15:45 15 min break  
15:45 - 16:15 Poster blizz #1-P (Amphi Blaise Pascal) (Chair: Bertrand Iooss)  
  Supervised deep learning for stochastic lid-driven cavity flows (Fabio Musco)   
  Uncertainty analysis as an ally for deep-learning-based hybridization of simulation codes (Paul Novello)   
  Uncertainty quantification and multivariate functional data: an application to the supervised classification of augmented plane trajectories (Rémi Perrichon)   
  Uncertainty quantification in polysilicon-based MEMS: a representation learning comparison (Jose Pablo Quesada-Molina)   
  Dealing with confusing samples into learning based model applied to image classification (Jiarui Xie)   
  Comparing different methods of sensitivity analysis for computational modelling of magnesium-based implant biodegradation (Tamadur Albaraghtheh)   
  How do the soil, the vegetation and the weather affect the water content of a green roof? (Axelle Hégo)   
  Bayesian NVH metamodels to assess "pre-design" interior cabin noise using measurement databases (Vinay Prakash)   
  Damage detection and localization for SVI in floating-slab track: a domain adaptation-based method (Zhandong Yuan)   
  Statistical Parameter Calibration using Bayesian Inference applied to a Finite Element Model (Tizian Zeckey)   
15:45 - 16:15 Poster blizz #1-V (Amphi Vinci) (Chair: Olivier Roustant)  
  Bayesian multi-objective optimization for quantitative risk assessment in microbiology (Subhasish Basak)   
  Shapley effect estimation in reliability-oriented sensitivity analysis with correlated inputs by importance sampling (Julien Demange-Chryst)   
  Multifidelity surrogate modelling with noisy grey-box models (Aikaterini Giannoukou)   
  Statistical methods for the study of computer experiments failures: application to a fuel-coolant interaction simulation code (Faouzi Hakimi)   
  Robust adaptation of the train speed for energy saving under punctuality and security constraints (Julien Nespoulous)   
  A novel strategy to surrogate the transient response of wind turbine simulations (Styfen Schär)   
  Sensitivity to statistical estimation uncertainties and probabilistic model identification (Charles Surget)   
  Sequential Bayesian inversion of black-box functions in presence of uncertainties (Romain Ait Abdelmalek-Lomenech)   
  A SUR version of the Bichon criterion for inversion (Clément Duhamel)   
  Supervised learning and Monte Carlo Markov Chain methods for inverse problem resolution in random neutronics (Paul Lartaud)   
16:15 - 16:45 Coffee break  
16:45 - 17:09 Poster blizz #2-P (Amphi Blaise Pascal) (Chair: Anthony Nouy)  
  A scalable benchmark for multidisciplinary design optimization under uncertainty (Amine Aziz Alaoui)   
  Deterministic optimisation in Deep Learning from a continuous and energetic point of view (Bilel Bensaid)   
  Mixture kriging on granular data (Marc Grossouvre)   
  Robustness assessment using quantile-constrained Wasserstein projections (Marouane Il Idrissi)   
  Auto-associative models, a generalized PCA (Valentin Pibernus)   
  Gaussian processes indexed by clouds of points: a study (Babacar Sow)   
  Transfer learning of statistical models on Riemannian manifolds (Tien Tam Tran)   
  Gaussian process based reachability analysis (Ke Wang)   
16:45 - 17:12 Poster blizz #2-V (Amphi Vinci) (Chair: Clémentine Prieur)  
  Physics informed neural networks for inverse uncertainty quantification of material elastic properties on a simple 2D beam example (Damien Bonnet-Eymard)   
  Grey-box modelling for near-real time online monitoring of dynamic processes (Miriam Beatrice Dodt)   
  Physics-informed random fields. Application to kriging (Iain Henderson)   
  Adapted line sampling and neural networks for evaluating the info-gap robustness of reliability estimates for penstocks (Antoine Ajenjo)   
  Kriging adaptive learning for high dimensional reliability assessment with a variance-based learning and stopping criterion (Gabriele Capasso)   
  Adaptive importance sampling for reliability assessment of an industrial system modeled by a piecewise deterministic Markov process (Guillaume Chennetier)   
  Kernel-based sequential quadrature methods applied to offshore wind turbine damage estimation (Elias Fekhari)   
  Uncertainty quantification and global sensitivity analysis of seismic fragility curves using kriging (Clément Gauchy)   
  Improved cross entropy method with Bernoulli mixture model (Jianpeng Chan)   
17:15 - 18:00 Presentation of the institutional sponsors (chair: Rodolphe Le Riche)  
  MASCOT-NUM research group (Anthony Nouy)
  Université Franco-Allemande (Sandra Reuther)
  Agence Maths Entreprise Société AMIES (Magalie Fredoc)  
  Fédération Maths Auvergne Rhône-Alpes MARA (Catherine Aaron)
18:00 - 18:45 Poster session (held in main lobby, ground floor)  
18:30 - 19:30 Cocktail (next door to main lobby, ground floor)  
20:15 - 22:45 Conference dinner (1st group)  

Wednesday, June 8, 2022


09:00 - 10:30 Course (1/2) - Uncertainty quantification in machine learning (Eyke Hüllermeier) (Chairs: Jean-Marc Bourinet, Josselin Garnier)      
10:30 - 11:00 Coffee break  
11:00 - 11:45 Inv talk #2 - Learning to predict complex outputs: a kernel view (Florence D’Alché Buc) (Chairs: Chafik Samir, Céline Helbert)     
11:45 - 12:30 Inv talk #3 - Representing non-negative functions, with applications in non-convex optimization and beyond (Alessandro Rudi) (cancelled)
12:30 - 14:00 Lunch  
14:00 - 14:45 Inv talk #4 - Multiphysics system analysis and optimization under uncertainty (Mathieu Balesdent) (Chairs: Carsten Proppe, Bruno Sudret)     
14:45 - 15:30 Inv talk #5 - Reliability sensitivity analysis with dependent inputs (Iason Papaioannou) (Chairs: Julien Bect, Sonja Kuhnt)     
15:30 - 16:15 Inv talk #6 - Sensitivity of uncertainty quantification and Bayesian inverse problems (Björn Sprungk) (Chairs: Clémentine Prieur, Bruno Sudret )     
16:15 - 16:45 Coffee break  
16:45 - 17:30 Inv talk #7 - Inverse state and parameter estimation: optimal algorithms and applications (Olga Mula)  (Chairs: Luc Pronzato, Daniel Straub)     
17:30 - 18:15 Inv talk #8 - Uncertainty quantification and Bayesian inference for fractional diffusion models (Olivier Le Maître)  (Chairs: Mireille Bossy, Olivier Roustant)     
18:15 - 19:00 Challenges as seen by our technical sponsors  (Chairs: Cécile Mattrand, Guillaume Perrin)  
  Consortium in applied maths CIROQUO (Céline Helbert)
  IFPEN (Delphine Sinoquet, Miguel Munoz Zuniga)
  Safran Tech (Sébastien Da Veiga)  
  Michelin (François Deheeger)
20:15 - 22:45 Conference dinner (2nd group)  

Thursday, June 9, 2022


09:00 - 10:30 Course (2/2) - Uncertainty quantification in machine learning (Eyke Hüllermeier)  (Chairs: Jean-Marc Bourinet, Luc Pronzato)     
10:30 - 11:00 Coffee break  
11:00 - 11:45 Inv talk #9 - Consensus-based optimization (Claudia Totzeck)  (Chairs: Miguel Munoz Zuniga, Mickaël Binois)     
11:45 - 12:30 Inv talk #10 - Bayesian inference: interacting particle approaches (Sebastian Reich)  (Chairs: Catherine Aaron, Christophette Blanchet-Scalliet)     
12:30 - 12:45 Closure speech (MASCOT-NUM research group)  
12:45 - 14:00 Lunch  
Online user: 2 Privacy
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