Summary
I work at the intersection of computational statistics, machine learning, and generative modelling. A proper summary can be found on my webpage.
Publications
Journals
Akyildiz OD, Crisan D, Miguez J, 2024, Sequential discretisation schemes for a class of stochastic differential equations and their application to bayesian filtering, Siam Journal on Numerical Analysis, ISSN:0036-1429
Akyildiz OD, 2024, Global convergence of optimized adaptive importance samplers, Foundations of Data Science, ISSN:2639-8001
Akyildiz OD, Sabanis S, 2024, Nonasymptotic analysis of Stochastic Gradient Hamiltonian Monte Carlo under local conditions for nonconvex optimization, Journal of Machine Learning Research, ISSN:1532-4435
Vadeboncoeur A, Akyildiz OD, Kazlauskaite I, et al., 2023, Fully probabilistic deep models for forward and inverse problems in parametric PDEs, Journal of Computational Physics, Vol:491, ISSN:0021-9991, Pages:1-25
Elvira V, Chouzenoux É, Akyildiz OD, et al., 2023, Gradient-based adaptive importance samplers, Journal of the Franklin Institute, Vol:360, ISSN:0016-0032, Pages:9490-9514