Publications

• Cao, H., Cohen, S. and Szpruch, L., 2021. Identifiability in inverse reinforcement learning. Advances in Neural Information Processing Systems, 34, pp.12362-12373. NeurIPS Proceedings
• Kerimkulov, B., Siska, D. and Szpruch, L., 2021. A modified MSA for stochastic control problems. Applied Mathematics & Optimization, 84(3), pp.3417-3436. arXiv
• Ni, H., Szpruch, L., Sabate-Vidales, M., Xiao, B., Wiese, M. and Liao, S., 2021, November. Sig-Wasserstein GANs for time series generation. In Proceedings of the Second ACM International Conference on AI in Finance (pp. 1-8).arXiv
• Sabate Vidales, M., SiSka, D. and Szpruch, L., 2021. Unbiased Deep Solvers for Linear Parametric PDEs. Applied Mathematical Finance, pp.1-31.arXiv
• Cohen, S.N., Snow, D. and Szpruch, L., 2021. Black-box model risk in finance. book chapter in Machine Learning And Data Sciences For Financial Markets: A Guide To Contemporary Practices, Cambridge University Press 2022. arXiv
• Arribas I.P., Salvi C., Szpruch L., Sig-SDEs model for quantitative finance, proceedings of ICAIF 2020. arXiv
• Duncan A., Nusken N., Szpruch L., On the geometry of Stein variational gradient descent, JMLR, 2021 arXiv
• Kaitong H., Zhenjie R., Siska., Szpruch L., Mean-Field Langevin Dynamics and Energy Landscape of Neural Networks, Ann. Inst. H. Poincaré Probab. Statist., 2021 arXiv
• Szpruch L., Tse A., Antithetic multilevel particle system sampling method for McKean-Vlasov SDEs, The Annals of Applied Probability 31.3 (2021): 1100-1139. arXiv
• Chassagneux JF., Szpruch L., Tse A., Weak quantitative propagation of chaos via differential calculus on the space of measures, The Annals of Applied Probability, 32(3), pp.1929-1969., 2022 arXiv
• Hammersley R. P. W, Siska D., Szpruch L., McKean-Vlasov SDEs under Measure Dependent Lyapunov Conditions, Ann. Inst. H. Poincaré Probab. Statist., 57(2), 1032-1057, 2021 journal, arXiv
• Kerimkulov B., Siska D., Szpruch L., A modified MSA for stochastic control problems, Applied Mathematics & Optimization, 2021 journal, arXiv
• Hammersley R. P. W, Siska D., Szpruch L., Weak Existence and Uniqueness for McKean-Vlasov SDEs with Common Noise, Annals of Probability, 49(2), 527-555, 2021 arXiv
• Kerimkulov B., Siska D., Szpruch L., Exponential Convergence and stability of Howards's Policy Improvement Algorithm for Controlled Diffusions, SIAM J. Control Optim., 58(3), 1314–1340. journal,arXiv
• Majka M.B., Mijatovic A., Szpruch L, Non-asymptotic bounds for sampling algorithms without log-concavity, to appear in Annals of Applied Probability, arXiv
• Giles M.B., B. Majka M.B., Szpruch L, Vollmer S., Zygalakis K., Multilevel Monte Carlo methods for the approximation of invariant measures of stochastic differential equations, Statistics and Computing, 2019 arXiv
• Szpruch L., Tan S., Tse A., Iterative Particle Approximation for McKean-Vlasov SDEs with application to Multilevel Monte Carlo estimation, Annals of Applied Probability Volume 29, Number 4 (2019), 2230-2265. journal, arXiv
• Neuenkirch A., Szolgyenyi M, Szpruch L., An adaptive Euler-Maruyama scheme for stochastic differential equations with discontinuous drift and its convergence analysis, SIAM J. Numer. Anal. 57-1 (2019), pp. 378-403. journal, arXiv
• AlRachid H., Bossy M., Ricci C., Szpruch L., New particle representations for ergodic McKean-Vlasov SDEs, ESAIM: ProcS Volume 65, 2019 journal, arXiv
• Szpruch, L. Zhang, X. V-Integrability, Asymptotic Stability And Comparison Theorem of Explicit Numerical Schemes for SDEs, Mathematics of Computations 87 (2018), 755-783 , arXiv
• Lionnet A., dos Reis G. and Szpruch L., Convergence and qualitative properties of modified explicit schemes for BSDEs with polynomial growth , Annals of Applied Probability. Volume 28, Number 4 (2018), 2544-2591., journal arXiv
• Lionnet, A., dos Reis, G and Szpruch, L., Time discretisation of FBSDE with polynomial growth drivers and reaction-diffusion PDEs, Annals of Applied Probability, Vol. 25, 2563-2625, Number 5, 2015. arXiv
• Giles, M.B. and Szpruch, L., Antithetic multilevel Monte Carlo estimation for multi-dimensional SDEs without L\'{e}vy area simulation, Annals of Applied Probability, Vol. 24, 1585-1620 , Number 4 2014. arXiv
• Neuenkirch, A. and Szpruch, L., First order strong approximations of scalar SDEs with values in a domain, Numerische Mathematik, Vol. 128-1, pp 103-136, 2014. arXiv
• Higham, D.J., Mao, X. and Szpruch, L. Convergence, non-negativity and stability of a new Milstein Scheme with applications to finance, DCDS-B,18(8):2083 - 2100, AIMS, 2013 arXiv
• Giles, M.B. and Szpruch, L, Antithetic multilevel Monte Carlo estimation of financial options in Monte Carlo and Quasi-Monte Carlo Methods 2012. arXiv
• Cohen, S.N. and Szpruch, L. On Markovian Solutions to Markov Chain BSDEs Numerical Algebra, Control and Optimization, 2012, 2(2):257-269 arXiv
• Cohen, S.N. and Szpruch, L. A limit order book model for latency arbitrage, Mathematics and Financial Economics, 6(3):211-227, 2012. arXiv
• Dereich, S., Neuenkirch, A. and Szpruch, L., An Euler-type method for the strong approximation of the Cox–Ingersoll–Ross process, Proceedings of the Royal Society A, Vol. 468, No. 2140, pp. 1105–1115, 2012. arXiv
• Mao X., and Szpruch L., Strong convergence and stability of implicit numerical methods for stochastic differential equations with non-globally Lipschitz continuous coefficients, Journal of Computational and Applied Mathematics, 238:14-28,2013 arXiv
• Szpruch, L. and Mao. X., Strong convergence rates for backward Euler-Maruyama method for dissipative-type stochastic differential equations with super-linear diffusion coefficients, Stochastics, 85, no. 1, 144171, 2013. preprint
• Higham, D. J. , Intep, S., Mao, X., and Szpruch, L., Hybrid Simulation of auto-regulation within transcription and translation, BIT Numer Math., Vol. 51, No. 1, pp. 177-196, 2011.
• Szpruch, L. Mao X., Higham, D. J., and Pan, J., Numerical simulation of a strongly nonlinear Ait- Sahalia-type interest rate model, BIT Numer Math, Vol. 51, No. 2, pp. 405-425, 2011.
• Wu, F., Mao, X. and Szpruch L., Almost sure exponential stability of numerical solutions for stochastic delay differential equations, Numerische Mathematik, Vol. 115, No. 4, pp. 681-697, 2010.
• Szpruch, L., Higham, D. J., Comparing hitting time behavior of Markov jump processes and their diffusion approximations, Multiscale Model. Simul., No. 8, pp. 605-621, 2010.