no code implementations • 20 Nov 2023 • Harold Erbin, Riccardo Finotello
We review advancements in deep learning techniques for complete intersection Calabi-Yau (CICY) 3- and 4-folds, with the aim of understanding better how to handle algebraic topological data with machine learning.
no code implementations • 7 Oct 2022 • Riccardo Finotello, Daniel L'Hermite, Celine Quéré, Benjamin Rouge, Mohamed Tamaazousti, Jean-Baptiste Sirven
The procedure is an end-to-end pipeline including the process of synthetic data augmentation, the construction of a suitable robust, homoscedastic, deep learning model, and the validation of its predictions.
no code implementations • 30 Nov 2021 • Riccardo Finotello, Mohamed Tamaazousti, Jean-Baptiste Sirven
Laser-induced breakdown spectroscopy is a preferred technique for fast and direct multi-elemental mapping of samples under ambient pressure, without any limitation on the targeted element.
2 code implementations • 4 Aug 2021 • Harold Erbin, Riccardo Finotello, Robin Schneider, Mohamed Tamaazousti
We continue earlier efforts in computing the dimensions of tangent space cohomologies of Calabi-Yau manifolds using deep learning.
1 code implementation • 30 Jul 2020 • Harold Erbin, Riccardo Finotello
99%) accuracy for $h^{1, 1}$ using a neural network inspired by the Inception model for the old dataset, using only 30% (resp.
2 code implementations • 27 Jul 2020 • Harold Erbin, Riccardo Finotello
We introduce a neural network inspired by Google's Inception model to compute the Hodge number $h^{1, 1}$ of complete intersection Calabi-Yau (CICY) 3-folds.