Forecasting through deep learning and modal decomposition in multi-phase concentric jets. - León Mata; Rodrigo Abadía-Heredia; Manuel López Martín; José Miguel Pérez; Soledad Le Clainche (CoRR, 2022)

A predictive hybrid reduced order model based on proper orthogonal decomposition combined with deep learning architectures. - Rodrigo Abadía-Heredia; Manuel López Martín; Belén Carro; Juan Ignacio Arribas; José Miguel Pérez; Soledad Le Clainche (Expert Syst. Appl., 2022)

ModelFLOWs-app: data-driven post-processing and reduced order modelling tools. - Ashton Hetherington; Adrián Corrochano; Rodrigo Abadía-Heredia; Eneko Lazpita; Eva Muñoz; Paula Díaz; Egoitz Moira; Manuel López Martín; Soledad Le Clainche (CoRR, 2023)

Forecasting through deep learning and modal decomposition in two-phase concentric jets. - León Mata; Rodrigo Abadía-Heredia; Manuel López Martín; José Miguel Pérez; Soledad Le Clainche (Expert Syst. Appl., 2023)

Exploring the efficacy of a hybrid approach with modal decomposition over fully deep learning models for flow dynamics forecasting. - Rodrigo Abadía-Heredia; Adrián Corrochano; Manuel López Martín; Soledad Le Clainche (CoRR, 2024)

ModelFLOWs-app: Data-driven post-processing and reduced order modelling tools. - Ashton Hetherington; Adrián Corrochano; Rodrigo Abadía-Heredia; Eneko Lazpita; Eva Muñoz; Paula Díaz; Egoitz Maiora; Manuel López Martín; Soledad Le Clainche (Comput. Phys. Commun., 2024)

Hybrid machine learning models based on physical patterns to accelerate CFD simulations: a short guide on autoregressive models. - Arindam Sengupta; Rodrigo Abadía-Heredia; Ashton Hetherington; José Miguel Pérez; Soledad Le Clainche (CoRR, 2025)

An Adaptive Framework for Autoregressive Forecasting in CFD Using Hybrid Modal Decomposition and Deep Learning. - Rodrigo Abadía-Heredia; Manuel López Martín; Soledad Le Clainche (CoRR, 2025)