no code implementations • 29 Sep 2022 • Xinyu Zhou, Jun Zhao, Huimei Han, Claude Guet
Federated Learning (FL) is an intriguing distributed machine learning approach due to its privacy-preserving characteristics.
no code implementations • 9 Dec 2021 • Zhe Wang, Nicolas Privault, Claude Guet
We present an algorithm for the calibration of local volatility from market option prices through deep self-consistent learning, by approximating both market option prices and local volatility using deep neural networks, respectively.
no code implementations • 4 Aug 2021 • Zhe Wang, Claude Guet
We introduce a self-consistent deep-learning framework which, for a noisy deterministic time series, provides unsupervised filtering, state-space reconstruction, identification of the underlying differential equations and forecasting.
no code implementations • 11 May 2021 • Zhe Wang, Claude Guet
The present work's objective is two-fold, first to show how an a priori knowledge can be incorporated into neural networks to achieve efficient learning and second to apply the method and study how the induced field and polarizability change when a dielectric particle progressively changes its shape from a sphere to a cube.