Conditional time series forecasting with convolutional neural networks A Borovykh, S Bohte, CW Oosterlee Journal of Computational Finance 22 (4), 2017 | 828* | 2017 |
A neural network-based framework for financial model calibration S Liu, A Borovykh, LA Grzelak, CW Oosterlee Journal of Mathematics in Industry 9 (1), 9, 2019 | 139 | 2019 |
Optimally weighted loss functions for solving pdes with neural networks R van der Meer, C Oosterlee, A Borovykh Journal of Computational and Applied Mathematics, 2020 | 137 | 2020 |
Generalization in fully-connected neural networks for time series forecasting A Borovykh, CW Oosterlee, SM Bohté Journal of Computational Science 36, 101020, 2019 | 43 | 2019 |
Honest-but-curious nets: Sensitive attributes of private inputs can be secretly coded into the classifiers' outputs M Malekzadeh, A Borovykh, D Gündüz Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications …, 2021 | 41 | 2021 |
Layer-wise characterization of latent information leakage in federated learning F Mo, A Borovykh, M Malekzadeh, H Haddadi, S Demetriou Distributed and Private Machine Learning (DPML) Workshop ICLR, 2020 | 28 | 2020 |
A Gaussian Process perspective on Convolutional Neural Networks A Borovykh arXiv preprint arXiv:1810.10798, 2018 | 21 | 2018 |
Quantifying and Localizing Usable Information Leakage from Neural Network Gradients F Mo, A Borovykh, M Malekzadeh, S Demetriou, D Gündüz, H Haddadi arXiv preprint arXiv:2105.13929, 2022 | 20* | 2022 |
Efficient computation of various valuation adjustments under local Lévy models A Borovykh, A Pascucci, CW Oosterlee SIAM Journal on Financial Mathematics 9 (1), 251-273, 2018 | 20 | 2018 |
On stochastic mirror descent with interacting particles: convergence properties and variance reduction A Borovykh, N Kantas, P Parpas, GA Pavliotis Physica D: Nonlinear Phenomena 418, 132844, 2021 | 17 | 2021 |
Pricing Bermudan options under local Lévy models with default A Borovykh, A Pascucci, CW Oosterlee Journal of Mathematical Analysis and Applications 450 (2), 929-953, 2017 | 16 | 2017 |
On a neural network to extract implied information from American options S Liu, Á Leitao, A Borovykh, CW Oosterlee Applied Mathematical Finance 28 (5), 449-475, 2021 | 13* | 2021 |
Systemic risk in a mean-field model of interbank lending with self-exciting shocks A Borovykh, A Pascucci, S La Rovere IISE Transactions 50 (9), 806-819, 2018 | 12 | 2018 |
Leave-one-out distinguishability in machine learning J Ye, A Borovykh, S Hayou, R Shokri International Conference on Learning Representations (ICLR) 2024, 2024 | 8 | 2024 |
To interact or not? The convergence properties of interacting stochastic mirror descent A Borovykh, N Kantas, P Parpas, GA Pavliotis International Conference on Machine Learning (ICML) Workshop on ‘Beyond …, 2020 | 7 | 2020 |
Data-driven initialization of deep learning solvers for Hamilton-Jacobi-Bellman PDEs A Borovykh, D Kalise, A Laignelet, P Parpas 25th International Symposium on Mathematical Theory of Networks and Systems …, 2022 | 5 | 2022 |
Stochastic Mirror Descent for Convex Optimization with Consensus Constraints A Borovykh, N Kantas, P Parpas, GA Pavliotis SIAM Journal on Applied Dynamical Systems, 2024 | 4* | 2024 |
Optimizing interacting Langevin dynamics using spectral gaps A Borovykh, N Kantas, P Parpas, G Pavliotis International Conference on Machine Learning (ICML) Workshop on “Beyond …, 2021 | 4 | 2021 |
CHAROT: Robustly controlling chaotic PDEs with partial observations M Weissenbacher, A Borovykh, G Rigas ICLR 2024 Workshop on AI4DifferentialEquations In Science, 2024 | 2 | 2024 |
Username Squatting on Online Social Networks: A Study on X A Lepipas, A Borovykh, S Demetriou 19th ACM ASIA Conference on Computer and Communications Security (ACM AsiaCCS), 2024 | 2 | 2024 |