Machine learning for complete intersection Calabi-Yau manifolds: a methodological study. - Harold Erbin; Riccardo Finotello (CoRR, 2020)

HyperPCA: a Powerful Tool to Extract Elemental Maps from Noisy Data Obtained in LIBS Mapping of Materials. - Riccardo Finotello; Mohamed Tamaazousti; Jean-Baptiste Sirven (CoRR, 2021)

Inception neural network for complete intersection Calabi-Yau 3-folds. - Harold Erbin; Riccardo Finotello (Mach. Learn. Sci. Technol., 2021)

Trustworthiness of Laser-Induced Breakdown Spectroscopy Predictions via Simulation-based Synthetic Data Augmentation and Multitask Learning. - Riccardo Finotello; Daniel L'Hermite; Celine Quéré; Benjamin Rouge; Mohamed Tamaazousti; Jean-Baptiste Sirven (CoRR, 2022)

Deep multi-task mining Calabi-Yau four-folds. - Harold Erbin; Riccardo Finotello; Robin Schneider; Mohamed Tamaazousti (Mach. Learn. Sci. Technol., 2022)

Functional renormalization group for signal detection and stochastic ergodicity breaking. - Harold Erbin; Riccardo Finotello; Bio Wahabou Kpera; Vincent Lahoche; Dine Ousmane Samary (CoRR, 2023)

Deep learning complete intersection Calabi-Yau manifolds. - Harold Erbin; Riccardo Finotello (CoRR, 2023)

Robustness of Tensor Decomposition-Based Neural Network Compression. - Théo Rudkiewicz; Mohamed Ouerfelli; Riccardo Finotello; Zakariya Chaouai; Mohamed Tamaazousti (ICIP, 2024)

Functional Renormalization for Signal Detection: Dimensional Analysis and Dimensional Phase Transition for Nearly Continuous Spectra Effective Field Theory. - Riccardo Finotello; Vincent Lahoche; Dine Ousmane Samary (CoRR, 2025)