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日仏数学拠点FJ-LMIセミナー
過去の記録 ～02/05｜次回の予定｜今後の予定 02/06～
| 担当者 | 小林俊行, ミカエル ペブズナー |
|---|
過去の記録
2024年01月23日(火)
13:30-14:40 数理科学研究科棟(駒場) 118号室
Antoine DIEZ 氏 (京都大学, Kyoto University, ASHBi)
Particle systems with geometrical constraints and applications (英語)
https://fj-lmi.cnrs.fr/seminars/
Antoine DIEZ 氏 (京都大学, Kyoto University, ASHBi)
Particle systems with geometrical constraints and applications (英語)
[ 講演概要 ]
Since the pioneering work of Boltzmann, statistical physics has moti-vated the mathematical study or large systems of interacting particles, especially at the interface between stochastic analysis and PDE. More recently, there has been a surge of interest to consider applications to life sciences, where particles can be seen as convenient modeling entities to represent e.g. cell aggregates, bacterial swarms or animal societies. An important question in this context is the link between the microscopic agent-based description and the macroscopic continuum PDE description. Unlike physical systems which generally obey conservation laws, biological systems are rather subjects to constraints which are more geometrical in nature: volume constraints, shape or internal structure for instance. This poses a number of challenges on the modeling, analytical and numerical aspects. In this talk, I will first review earlier works on the study of particle systems with geometrical constraints. Then I will introduce a new framework, based on optimal transport theory, to model particles with arbitrary shapes and deformability properties. I will discuss potential applications in biology and compare this novel approach to other more classical methods.
[ 講演参考URL ]Since the pioneering work of Boltzmann, statistical physics has moti-vated the mathematical study or large systems of interacting particles, especially at the interface between stochastic analysis and PDE. More recently, there has been a surge of interest to consider applications to life sciences, where particles can be seen as convenient modeling entities to represent e.g. cell aggregates, bacterial swarms or animal societies. An important question in this context is the link between the microscopic agent-based description and the macroscopic continuum PDE description. Unlike physical systems which generally obey conservation laws, biological systems are rather subjects to constraints which are more geometrical in nature: volume constraints, shape or internal structure for instance. This poses a number of challenges on the modeling, analytical and numerical aspects. In this talk, I will first review earlier works on the study of particle systems with geometrical constraints. Then I will introduce a new framework, based on optimal transport theory, to model particles with arbitrary shapes and deformability properties. I will discuss potential applications in biology and compare this novel approach to other more classical methods.
https://fj-lmi.cnrs.fr/seminars/
2023年12月04日(月)
14:00- 数理科学研究科棟(駒場) 056号室
Philippe G. LEFLOCH 氏 (Sorbonne University & CNRS)
An introduction to Einstein constraints and the seed-to-solution method
https://fj-lmi.cnrs.fr/seminars/
Philippe G. LEFLOCH 氏 (Sorbonne University & CNRS)
An introduction to Einstein constraints and the seed-to-solution method
[ 講演概要 ]
I will present an introduction to the constraint equations associated with Einstein’s field equations of general relativity, and to recent developments based on the seed-to-solution method developed in collaboration with The-Cang Nguyen (Montpellier) and Bruno Le Floch (LPTHE, Sorbonne).
[ 講演参考URL ]I will present an introduction to the constraint equations associated with Einstein’s field equations of general relativity, and to recent developments based on the seed-to-solution method developed in collaboration with The-Cang Nguyen (Montpellier) and Bruno Le Floch (LPTHE, Sorbonne).
https://fj-lmi.cnrs.fr/seminars/
2023年11月28日(火)
16:00- 数理科学研究科棟(駒場) 117号室
Maud DELATTRE 氏 (Université Paris-Saclay, INRAE)
Some contributions on variable selection in nonlinear mixed-effects models
https://fj-lmi.cnrs.fr/seminars/
Maud DELATTRE 氏 (Université Paris-Saclay, INRAE)
Some contributions on variable selection in nonlinear mixed-effects models
[ 講演概要 ]
In the first part of this presentation, we will introduce the general formalism of nonlinear mixed effects models (NLMEM) that are specifically designed models to describe dynamic phenomena from repeated data on several subjects. In the second part, we will focus on specific variable selection technics for NLMEM through two contributions. In the first one, we will discuss the proper definition and use of the Bayesian information criterion (BIC) for variable selection in a low dimensional setting. High dimensional variable selection is the subject of the second contribution.
References
[1] Delattre, M., Lavielle, M. and Poursat, M.A. (2014) A note on BIC in mixed effects models, Electronic Journal of Statistics 8(1) p. 456-475.
[2] Delattre, M. and Poursat, M.A. (2020) An iterative algorithm for joint covariate and random effect selection in mixed effects models., The International Journal of Biostatistics 16(2), 20190082.
[3] Naveau, M., Kon Kam King, G., Rincent, R., Sansonnet, L. and Delattre, M. Bayesian high dimensional covariate selection in non-linear mixed-effects models using the SAEM algorithm. hal-03685060.
[ 講演参考URL ]In the first part of this presentation, we will introduce the general formalism of nonlinear mixed effects models (NLMEM) that are specifically designed models to describe dynamic phenomena from repeated data on several subjects. In the second part, we will focus on specific variable selection technics for NLMEM through two contributions. In the first one, we will discuss the proper definition and use of the Bayesian information criterion (BIC) for variable selection in a low dimensional setting. High dimensional variable selection is the subject of the second contribution.
References
[1] Delattre, M., Lavielle, M. and Poursat, M.A. (2014) A note on BIC in mixed effects models, Electronic Journal of Statistics 8(1) p. 456-475.
[2] Delattre, M. and Poursat, M.A. (2020) An iterative algorithm for joint covariate and random effect selection in mixed effects models., The International Journal of Biostatistics 16(2), 20190082.
[3] Naveau, M., Kon Kam King, G., Rincent, R., Sansonnet, L. and Delattre, M. Bayesian high dimensional covariate selection in non-linear mixed-effects models using the SAEM algorithm. hal-03685060.
https://fj-lmi.cnrs.fr/seminars/
2023年11月24日(金)
14:00-14:40 数理科学研究科棟(駒場) 117号室
Gwénaël MASSUYEAU 氏 (Université de Bourgogne & CNRS)
Surgery equivalence relations on 3-manifolds (English)
https://fj-lmi.cnrs.fr/seminars/
Gwénaël MASSUYEAU 氏 (Université de Bourgogne & CNRS)
Surgery equivalence relations on 3-manifolds (English)
[ 講演概要 ]
By some classical results in low-dimensional topology, any two 3-manifolds (with the “same” boundaries) are related one to the other by surgery operations. In this survey talk, we shall review this basic fact and, next, by restricting the type of surgeries, we shall consider several families of non-trivial equivalence relations on the set of (homeomorphism classes of) 3-manifolds. Those “surgery equivalence relations” are defined in terms of filtrations of the mapping class groups of surfaces, and their characterization / classification involves the notion of “finite-type invariant” which arises in quantum topology.
[ 講演参考URL ]By some classical results in low-dimensional topology, any two 3-manifolds (with the “same” boundaries) are related one to the other by surgery operations. In this survey talk, we shall review this basic fact and, next, by restricting the type of surgeries, we shall consider several families of non-trivial equivalence relations on the set of (homeomorphism classes of) 3-manifolds. Those “surgery equivalence relations” are defined in terms of filtrations of the mapping class groups of surfaces, and their characterization / classification involves the notion of “finite-type invariant” which arises in quantum topology.
https://fj-lmi.cnrs.fr/seminars/
