MEETINGS

Seminars are usually on Thursday morning at CMAP. To register on the mailing-list, see https://groups.io/g/ml

2020

  • Mar. 12, Hideatsu Tsukahara (Seijo Univ.): Minicourse on Statistics of Risk Measures: Estimation and Backtesting
  • Mar. 9, Hideatsu Tsukahara (Seijo Univ.): A Copula Approach to Spatial Econometrics with Applications to Finance
  • Feb. 27,
    • Dorinel Bastide (Ecole Polytechnique): Calculation of Credit Provision to CCP Exposures Using Expected Loss Approach
    • Cyril Benezet (Ecole Polytechnique): Deep Learning Approximations of Stochastic Control Problems and PDEs in High Dimension
  • Feb. 13, James Brice Scoggins (Ecole Polytechnique): Uniformly Accurate Machine Learning-based Hydrodynamic Models for Kinetic Equations
  • Feb. 6, Climate & Risk workshop
    • Vincent Bouchet (CDC and Ecole Polytechnique): Corporate Credit Risk Senstivity to Carbon Price
    • Edwin Mangin (BNPP - STMM): Introduction on Credit-climate Stress Test
    • Céline Guivarch (CIRED): Overview of Economic-climate Models
  • Jan. 30, Bruno Loureiro (IPhT): Are Generative Models the New Sparsity?
  • Jan. 9, Rodrigo Targino

2019

  • Nov. 28,
    • Siragan Gailus (Boston Univ.), Homogenization and Fluctuations for Diffusions with Standard and Fractional Browian Motion
    • Linda Chamakh (BNP Paribas): How many samples are needed to estimate a convolutional or recurrent neural network?
  • Nov. 21,
    • Jérôme Stenger (EDF): Optimal Uncertainty Quantification of a Risk Measurement on a Moment Class
    • Alex Lambert (Telecom ParisTech): Learning Function-valued Functions in RKHSs: Application to Integral Losses
  • Nov. 7,
    • Gwladys Toulemonde (Montpellier Univ.): Stochastic Modelling and Stimulation of Extreme Rainfalls
    • Bouazza Saadeddine (Evry Univ. and CACIB), Multi-task Learning as Multi-Objective Optimization
  • Oct. 24,
    • Rodrigo Targino (FGV Rio), Understanding the Economic Policy Uncertainty Index Using Semi-Automatic News Classification
    • Michaël Allouche (Ecole Polytechnique): Enriching Financial Datasets with GAN
  • Oct. 17, Rodrigo Targino (FGV Rio), Elements of Risk Management and the Allocation Problem: Abstract slides
  • Oct. 10, Pierre-Cyril Aubin-Frankowski (Mines ParisTech), Finding Mixed Nash Equilibria of Generative Adversarial Networks
  • Oct. 3, Philippe Durand (Banque de France), Financial Crisis and its Evaluation
  • Sept. 19, workshop day
  • Jun. 24, Jonas Peters  and Rune Christiansen (Univ. Copenhagen),Causality, in Data Sciences Initiative
  • Jun; 20, Nicolas Prost (Prevision.io), Local linear forests
  • Jun. 13,
    • Imke Mayer (Ecole polytechnique), Invariant Causal Prediction for Nonlinear Models
    • Clément Dombry (Univ. Franche-Comté), The coupling method in Extreme Value Theory
  • Jun. 6, Marcos Carreira (Ecole polytechnique), Learning Interest Rate Interpolation
  • May 28-29, International Workshop on Stress Test and Risk Management (stresstest2019) , Paris
  • May 21, Jérémy Fouliard (ENSAE), Answering the Queen: online machine learning and financial crisesMay 16, Kaitong Hu (Ecole polytechnique), Mean field Langevin dynamic and its applications to neural network
  • May 9,
    • Linda Chamakh (Ecole polytechnique), On the Margin Theory of Feedforward Neural Networks
    • Antoine Usseglio (INRIA), Estimation of conditional extreme risk measures from heavy-tailed elliptical random vector
  • Apr. 29, Elena A. Erosheva (Univ. Washington), Analyzing JSTOR corpus of publications: Is there gender homophily in scientific collaborations?
  • Rare Event Simulation Methods
  • Bouazza Saadeddine (Univ. Paris Saclay), Online natural gradient as a Kalman filter
  • Mar. 28, Frédéric Loge Munerel (ENSAI), Deep Knockoffs
  • Mar. 25, Tengyuan Leng (ENSAE), New Thoughts on Adaptivity, Generalization and Interpolation Motivated from Neural Networks
  • Mar. 21, Gildas Mazo (Univ. Paris-Saclay) , Sensitivity Analysis for Stochastic Models
  • Mar. 7,
    • Aude Sportisse (Univ. Pierre et Marie Curie), Variational Inference for Stochastic Block Models from Sampled Data
    • Guillaume Perrin (CEA), Uncertainty Quantification
  • Feb. 7,
    • Anne Sabourin (Ecole polytechnique), Binary Classification in Extreme Regions
    • Othmane Mounjid (Ecole polytechnique), Classification with Imperfect Training Labels
  • Feb. 6,
    • François Yvon (CNRS and LIMSI), Latest Techniques in Natural Language Understanding
    • Jean-Michel Loubes (IMT), Fairness in AI; Can everyday AI be ethical?
    • Sylvain Marsault (Carrefour DataLab), AI in retail
  • Feb. 4, Thomas Berrett (CREST and Univ. Cambridge), Efficient multivariate functional estimation and independence testing
  • Jan. 31, David Barrera (Ecole polytechnique), Two Strong Consistency Theorems for Nonparametric Regression Over Independent Samplings
  • Jan. 24, Geneviève Robin (Ecole polytechnique), Mean Field for the Stochastic Blockmodel: Optimization Landscape and Convergence Issues
  • Jan. 10, Stéphane Girard (minicourse), Intro. to Extreme-value Analysis: Application of Extreme-value Theory to Extrapolation (3/3)
  • Jan. 9, workshop day
    • Josselin Garnier (Ecole polytechnique), Introduction à la Meta-modélisation
    • Antoine Bezat (BNP Paribas), Eléments d’infrastructure méthodologique et aspect de l’exercice ST EBA
    • Stefano De Marco (BNP Paribas), Méthodes de Monte-Carlo multi-niveaux
    • Pierre Anton, Challenges pour le Reverse Stress Test Marché

2018

  • Dec. 13, Stéphane Girard (Ecole polytechnique), Intro. to Extreme-value Analysis: Maximum (2/3)
  • Nov. 29, Stéphane Girard (Ecole polytechnique), Introduction to Extreme-value Analysis (1/3)
  • Oct. 12, workshop day
    • Dorinal Bastide (BNP Paribas), Reverse stress test
    • Pierre Del Moral (Ecole Polytechnique), Méthodes Monte Carlo pour l’estimation et l’analyse de risque
    • Damien Hequet (BNP Paribas), Stress Test Credit
    • Emmanuel Gobet (Ecole Polytechnique), Quantification d’incertitudes des métriques de risque