| Nonasymptotic estimates for Stochastic Gradient Langevin Dynamics under local conditions in nonconvex optimization Y Zhang, ÖD Akyildiz, T Damoulas, S Sabanis Applied Mathematics & Optimization 87 (2), 1-41, 2023 | 82 | 2023 |
| VarGrad: a low-variance gradient estimator for variational inference L Richter, A Boustati, N Nüsken, FJR Ruiz, ÖD Akyildiz Advances in Neural Information Processing Systems (NeurIPS 2020) 33, 2020 | 79 | 2020 |
| Tweedie moment projected diffusions for inverse problems B Boys, M Girolami, J Pidstrigach, S Reich, A Mosca, OD Akyildiz Transactions of Machine Learning Research (TMLR), 2024 | 58 | 2024 |
| Nudging the particle filter ÖD Akyildiz, J Míguez Statistics and Computing 30 (2), 305-330, 2020 | 55 | 2020 |
| Convergence rates for optimised adaptive importance samplers ÖD Akyildiz, J Míguez Statistics and Computing 31 (2), 12, 2021 | 47 | 2021 |
| Fully probabilistic deep models for forward and inverse problems in parametric PDEs A Vadeboncoeur, ÖD Akyildiz, I Kazlauskaite, M Girolami, F Cirak Journal of Computational Physics 491, 112369, 2023 | 35 | 2023 |
| Generalized Bayesian Filtering via Sequential Monte Carlo A Boustati, ÖD Akyildiz, T Damoulas, AM Johansen Advances in Neural Information Processing Systems (NeurIPS 2020) 33, 2020 | 31 | 2020 |
| Nonasymptotic analysis of Stochastic Gradient Hamiltonian Monte Carlo under local conditions for nonconvex optimization OD Akyildiz, S Sabanis Journal of Machine Learning Research 25 (113), 1-34, 2024 | 29* | 2024 |
| Interacting particle Langevin algorithm for maximum marginal likelihood estimation ÖD Akyildiz, FR Crucinio, M Girolami, T Johnston, S Sabanis ESAIM: Probability and Statistics, 2025 | 28 | 2025 |
| On diffusion-based generative models and their error bounds: The log-concave case with full convergence estimates S Bruno, Y Zhang, DY Lim, ÖD Akyildiz, S Sabanis Transactions of Machine Learning Research (TMLR), 2025 | 22 | 2025 |
| Primal-dual algorithms for audio decomposition using mixed norms I Bayram, ÖD Akyıldız Signal, Image and Video Processing 8 (1), 95-110, 2014 | 21 | 2014 |
| Random grid neural processes for parametric partial differential equations A Vadeboncoeur, I Kazlauskaite, Y Papandreou, F Cirak, M Girolami, ... International Conference on Machine Learning, 34759-34778, 2023 | 18 | 2023 |
| Statistical finite elements via Langevin dynamics ÖD Akyildiz, C Duffin, S Sabanis, M Girolami SIAM/ASA Journal on Uncertainty Quantification 10 (4), 1560-1585, 2022 | 17 | 2022 |
| Gradient-based adaptive importance samplers V Elvira, E Chouzenoux, ÖD Akyildiz, L Martino Journal of the Franklin Institute 360 (13), 9490-9514, 2023 | 15 | 2023 |
| Φ-DVAE: Physics-informed dynamical variational autoencoders for unstructured data assimilation A Glyn-Davies, C Duffin, OD Akyildiz, M Girolami Journal of Computational Physics 515, 113293, 2024 | 14 | 2024 |
| Kinetic interacting particle Langevin Monte Carlo PFV Oliva, OD Akyildiz arXiv preprint arXiv:2407.05790, 2024 | 11 | 2024 |
| Adaptive noisy importance sampling for stochastic optimization OD Akyildiz, IP Marino, J Míguez 2017 IEEE 7th international workshop on computational advances in multi …, 2017 | 11 | 2017 |
| Proximal Interacting Particle Langevin Algorithms PC Encinar, FR Crucinio, OD Akyildiz Uncertainty in Artificial Intelligence (UAI), Oral presentation, Best …, 2025 | 10 | 2025 |
| Parallel sequential Monte Carlo for stochastic gradient-free nonconvex optimization ÖD Akyildiz, D Crisan, J Míguez Statistics and Computing, 2020 | 10 | 2020 |
| Global convergence of optimized adaptive importance samplers ÖD Akyildiz Foundations of Data Science (FoDS), 2024 | 9 | 2024 |
Joaquin MiguezDepartment of Signal Theory & Communications, Universidad Carlos III de MadridVerified email at tsc.uc3m.es
