WARIN Xavier

WARIN Xavier

The STochastic OPTimization library (StOpt)

https://gitlab.com/stochastic-control/StOpt

• "Distribution of a Stochastic Control Algorithm Applied to Gas Storage Valuation " (with C. Makassikis, S. Vialle) The 7th International Symposium on Signal Processing and Information Technology (ISSPIT-2007), IEEE Computer Society Press ,2007 [Publications] [2007]
   isspit-07-it_1714-makassikis-vialle-warin
• "A N-dimensional Stochastic Control Algorithm for Electricity Asset Management on PC cluster and Blue Gene Supercomputer" (with S Vialle, P Mercier) Workshop on State-of-the-Art in Scientific and Parallel Computing. Maximilien Germain,​_NTNU, Trondheim, NorwayMay 13-16, 2008 [Publications] [2008]
   para-2008-viallewarinmercier
• "Large Scale Distribution of Stochastic Control Algorithms for Financial Applications" (with C. Makassikis, S. Vialle), PDCoF08, pages 1-8, 2008-04 [Publications] [2008]
   pdcof-2008-makassikis-vialle-warin
• "Stochastic control optimization & simulation applied to energy management: From 1-D to N-D problem distributions, on clusters, supercomputers and Grids " (with S. Vialle, C. Makassikis, and P. Mercier) Grid@Mons conference, 2008 [Publications] [2008]
   lncs_warin_vialle_mercier
• "Large Scale Experiment and Optimization of a Distributed Stochastic Control Algorithm. Application to Energy Management Problems" (with P. Vezolle, S.Vialle) Workshop on Large-Scale Parallel Processing (LSPP 2009). Friday, May 29, 2009, Rome, Italy. [Publications] [2009]
   vezollewarinvialle_lspp_2009
• "Valuation of a powerplant under production constraints and markets incompleteness " (with A. Porchet, N. Touzi) Mathematical Methods of Operations research, Volume 70, Number 1 , pp 47-75, 2009. [Publications] [2009]
   ptwmmor
• "Design and Experimentation of a Large Scale Distributed Stochastic Control Algorithm Applied to Energy Management Problems" (with S Vialle) SBN 978-953-307-121-3, InTech, August 2010 [Articles de presse] [2010]
   chapter-mariva
• "A finite dimensional approximation for pricing moving average options" (with M Bernhart, P Tankov) SIAM Journal of Financial Mathematics Vol 2, pp 989-1013, 2011 [Publications] [2011]
   ma_options_r1
• " A Probabilistic Numerical Scheme for Fully Nonlinear PDEs " (with A. Fahim, N. Touzi) The Annals of Applied Probability, Vol 21, No 4, 1322-1364 [Publications] [2011]
   fahimtouziwarin-6avril2010
• "FT-GReLoSSS a Skeletal-Based Approach towards Application Parallelization and Low-Overhead Fault Tolerance" (with C. Makassikis, S Vialle), Proceedings of the 20th International Euromicro Conference PDP, 2012 [Publications] [2012]
  pdp2012_submission
• "Hedging swing contract on gas market" [Publications] [2012]
   swinggashedging
• "Gas storage hedging" , Numerical methods in finance, Springer [Publications] [2012]
   articlehedgingstockagegaz
• Swing option valuation : a BSDE with constrainted jumps approach" (with M Bernhart, H Pham, P Tankov) ,Numerical methods in finance, Springer  [Publications] [2012]
   swing_cjbsde_final_bptw
• "Monte-Carlo valorisation of American options: facts and new algorithms to improve existing methods" (with B Bouchard) Numerical methods in finance  [Publications] [2012]
   bouchardwarin
• Adaptive sparse grids for time dependent Hamilton-Jacobi-Bellman equations in stochastic control [Publications] [2014]
   hjb_sparse
• "Optimal Liquidity management and Hedging in the presence of a non-predictable investment opportunity" (with S. Villeneuve) Mathematics and Financial Economics (2014) 8: 193-227  [Publications] [2014]
   idei_osiris_optimalliquidity_version17122012
• "Numerical methods for the quadratic hedging problem in Markov models with jumps" (with C. De Franco, P. Tankov), Journal of Computational Finance, Volume 19, Number 2  [Publications] [2015]
   numerical_methods_for_the_quadratic_hedging_problem_in_markov_models_with_jumps_r2v3
• "Some non monotone schemes for time dependent Hamilton-Jacobi-Bellman equations in stochastic control", Journal of Scientific Computing, june 2015, pp 1-26 [Publications] [2015]
   hjb_jsc
• "Liquidity Management with Decreasing-returns-to-scale and Secured Credit Line" with Erwan Pierre and Stéphane Villeneuve, Finance and Stochastics,October 2016, Volume 20, Issue 4, pp 809–854
   fs14-2610-2ndeversion
• "The Asset Liability Management problem of a nuclear operator : a numerical stochastic optimization approach",  [Publications] [2016] alm_publication
• "Numerical approximation of a cash-constrained firm value with investment opportunities" (with Erwan Pierre, Stéphane Villeneuve),  SIAM Journal on Financial Mathematics , vol 8, issue 1  [2017]
   numericalapproximationsingular
• "Unbiased Monte Carlo estimate of stochastic differential equations expectations", with M. Doumbia and N. Oudjane, ESAIM P&S ,  21 (2017) 56-87 [Publications] [2017]
   BranchOW2016_Final
• "Variations on branching methods for non linear PDEs" , 2017,  VariationsOnBranching
• "Numerical approximation of BSDEs using local polynomial drivers and branching processes" , with Bruno Bouchard, Xiaolu Tan, Yiyi Zou, 2017, Monte Carlo Methods and Applications, 2017, vol. 23, no 4, p. 241-263   BTWZ1
• "Nesting Monte Carlo for high-dimensional Non Linear PDEs" , Monte Carlo Methods and Applications, volume 24, issue 4, 2018 ,  MCPDE_arxiv
• "Monte Carlo for high-dimensional degenerated SemiLinear and Full Non Linear PDEs", 2018, , MC2PDE_Arxiv
• "Branching diffusion representation of semilinear PDEs and Monte Carlo approximation" with Pierre Henry-Labordère, Nizar Touzi , Nadia Oudjane, Xiaolu Tan, Annales de l’Institut Henri Poincaré Probabilité Statistiques , Volume 55, Number 1 (2019), 184-210.  [2019]
   Branching_Semilinear_rev
• "Numerical approximation of general Lipschitz BSDEs with branching processes", with Bruno Bouchard, Xiaolu Tan, CEMRACS 2017 - Numerical methods for stochastic models: control, uncertainty quantification, mean-field, ESAIM: Proceedings and Surveys, Volume 65  , p 309 - 329, (2019)    BTW17
• "Variance optimal hedging with application to Electricity markets"   in Journal Of Computational Finance, volume 23, number 3, dec 2019   varHedging
• "Fast and stable multivariate kernel density estimation by fast sum updating", with Nicolas Langrené, Journal of Computational and Graphical Statistics ,Volume 28, 2019 - Issue 3, Pages 596-608 ,  fastKDE_JCGS_final
• "Regression Monte Carlo for microgrid management", with  Clémence Alasseur, Alexandro Balata, Sahar Ben Aziza, Aditya Maheshwari, Peter Tankov,  CEMRACS 2017 - Numerical methods for stochastic models: control, uncertainty quantification, mean-field, ESAIM: Proceedings and Surveys, Volume 65 , p 46 - 67, (2019) microgrid_proceedings_14092018
• "Machine Learning for semi linear PDEs" with  Chan-Wai-Nam, Q., Mikael, Journal of Scientific Computing, 79(3), 1667-1712,  2019, https://doi.org/10.1007/s10915-019-00908-3  ‡Machine_Learning_and_nesting_Monte_Carlo_for_semi_linear_PDEs
• "Some non monotone schemes for Hamilton Jacobi Bellman equations", CEMRACS 2017 - Numerical methods for stochastic models: control, uncertainty quantification, mean-field, ESAIM: Proceedings and Surveys, Volume 65 , p 476 - 497 (2019) hjb_2018_08
• "A power plant valuation under asymmetric risk criterion taking into acount maintenance costs", with Clémence Alasseur, Isaque Pimentel and Emmanuel Gobet, 2019   https://fime-lab.org/wp-content/uploads/2019/03/AssymRiskEnergy.pdf
• "Option valuation and hedging using asymmetric risk function: asymptotic optimality through fully nonlinear Partial Differential Equations", with Emmanuel gobet and Isaque Pimentel,  Finance Stoch (2020). https://doi.org/10.1007/s00780-020-00428-1 ,  paperAsymptotic
• "Some machine learning schemes for high-dimensional nonlinear PDEs", with Côme Huré and Huyên Pham, Mathematics of Computation, 89(324):1547–1579,  2020  BSDE_MachineLearning
• "On conditional cuts for Stochastic Dual Dynamic Programming",  2019, with Wim Van-Ackooij, EURO Journal on Computational Optimization 8.2 (2020): 173-199  CondCuts_SDDP_vanAckooij_Warin
• "Neural networks-based backward scheme for fully nonlinear PDEs" with Maximilien Germain, Huyên Pham,   SN Partial Differ. Equ. Appl. 2, 16 (2021). https://doi.org/10.1007/s42985-020-00062-8 ,FullNonLin-rev2   
• 'Risk management with machine learning based algorithms" , with Simon Fecamp and Joseph Mikael, 2021,  Journal of Computational Finance ,volume 25, number 2 Machine_Learning_for_Hedging_V2
• "Discretization and Machine Learning Approximation of BSDEs with a Constraint on the Gains-Process", with Idris Kharroubi and Thomas Lim, in "Monte Carlo Methods and Applications ", 2021 , https://doi.org/10.1515/mcma-2020-2080.   BSDEConst
• "Fast multivariate empirical cumulative distribution function with connection to kernel density estimation", with Nicolas Langrené,  "Computational Statistics and Data Analysis", vol 162, oct  2021 , Lap
• "Deep backward multistep schemes for nonlinear PDEsand approximation error analysis", with Maximilien Germain and Huyên Pham,  SIAM Journal on Scientific Computing 44.1 (2022), A28–A56,   MultiStepArXiv
• "Incentives, lockdown, and testing: from Thucydides’s analysis to the COVID–19 pandemic", with Emma Hubert, Thibault Mastrolia, Dylan Possamai,  Journal of mathematical biology 84.5 (2022)  NewCovid19_BIOMATH(1)
• "Numerical resolution of McKean-Vlasov FBSDEs using neuralnetworks", with Maximilien Germain, Joseph Mikael,  2022, Methodology and Computing in Applied Probability,  https://doi.org/10.1007/s11009-022-09946-1 MckeanVlassovFBDSE
• "Deep learning for efficient frontier calculation in finance",  Journal of Computational Finance, Vol. 26, No. 1, 2022,   MarkovitzALMIEtCeteraArticleVersionFeb2022JCF
• "DeepSets and their derivative networks for solving symmetric PDEs", with Maximilien Germain, Mathieu Laurière, and Huyên Pham ,  Journal of Scientific Computing , 91:63, 2022, https://doi.org/10.1007/s10915-022-01796-w DeepSetsSymPDE_JSCjournal
• "Rate of convergence for particles approximation of PDEs in Wasserstein space", with Maximilien Germain and Huyên Pham,  Journal of Applied Probability, 1-17. doi:10.1017/jpr.2021.102, 2022  ConvergencePDEWasserstein_JAP
• "A level-set approach to the control of state-constrained McKean-Vlasov equations: application to renewable energy storage and portfolio selection", with Maximilien Germain and Huyên Pham, Numerical Algebra, Control and Optimization, 2023, 13(3&4): 555-582. doi: 10.3934/naco.2022033     MKVconstrainedAIMS2022
• "The GroupMax neural network approximation of convex functions",  IEEE Transactions on Neural Networks and Learning Systems, 2023, convexArxiv
• "Reservoir optimization and Machine Learning methods",  EURO Journal on Computational Optimization, volume 11, 2023, https://doi.org/10.1016/j.ejco.2023.100068     StorageAndMachineLearningArxiv
• "Neural networks-based algorithms for stochastic control and PDEs in finance", with Maximilien Germain and Huyên Pham,  in  "Machine Learning for Financial Markets: a guide to contemporary practices, Cambridge University Press, Editors: Agostino Capponi and Charles-Albert Lehalle,Cambridge University Press, 2023   MLfinance_handbook
• "Quantile and moment neural networks for learning functionals of  distributions", 2023, Quantile_and_moment_networks
• "Neural networks for first order HJB equations and application to front propagation with obstacle terms" with Olivier Bokanowski and Averil Prost, Partial Differential Equations and Applications 4.5 , 2023,   BPW
• "A common shock model for multidimensinal electricity intraday price modelling with application to battery valuation" with Thomas Deschatre, 2023, jumps_correl_ij
• "Mean-field neural networks: learning mappings on Wasserstein space" with Huyên Pham,   Neural networks, 2023,  vol 168, pp 380-393,  https://doi.org/10.1016/j.neunet.2023.09.015,   LearningDistributionFinal
  
• "Actor critic learning algorithms for mean-field control with moment neural networks" with Huyên Pham, 2023,  ActorCriticNumNoEntrop
• "Deep Learning algorithms for FBSDEs with jumps : applications to option pricing and a MFG model for smart grids" with Clémence Alasseur, Zakaria Bensaid, Roxana Dumitrescu, 2024, MFG_Deep_merged_FBSDE
• "Neural networks for differential games", with Olivier Bokanowski, 2024, StationnaryGames-1
• "Mean-field neural networks-based algorithms for McKean-Vlasov control problems"  with Huyên Pham,  to appear in Journal of Machine Learning, 2024, , MasterEquation-1