Solving the Periodic Timetabling Problem using a Genetic Algorithm. - Diego Arenas; Remy Chevirer; Saïd Hanafi; Joaquin Rodriguez (CoRR, 2014)

Contributions on microscopic approaches to solve the train timetabling problem and its integration to the performance of infrastructure maintenance activities. (Contributions d'un modèle microscopique à la résolution du problème deconstruction d'une grille horaire et à la planification des activités demaintenance de l'infrastructure ferroviaire). - Diego Arenas (2016)

The Autonomous Train. - Damien Trentesaux; Rudy Dahyot; Abel Ouedraogo; Diego Arenas; Sébastien Lefebvre; Walter Schön; Benjamin Lussier; Hugues Cheritel (SoSE, 2018)

Timetable rearrangement to cope with railway maintenance activities. - Diego Arenas; Paola Pellegrini; Saïd Hanafi; Joaquin Rodriguez (Comput. Oper. Res., 2018)

Design choices for productive, secure, data-intensive research at scale in the cloud. - Diego Arenas; Jon Atkins; Clare Austin; David Beavan; Alvaro Cabrejas Egea; Stephen Carlysle-Davies; Ian Carter; Rob Clarke; James Cunningham; Tom Doel; Oliver Forrest; Evelina Gabasova; et al. (CoRR, 2019)

MLJ: A Julia package for composable machine learning. - Anthony D. Blaom; Franz J. Király; Thibaut Liénart; Yiannis Simillides; Diego Arenas; Sebastian J. Vollmer (J. Open Source Softw., 2020)

Crop Yield Prediction: An Operational Approach to Crop Yield Modeling on Field and Subfield Level with Machine Learning Models. - Patrick Helber; Benjamin Bischke; Peter Habelitz; Cristhian Sanchez; Deepak Pathak; Miro Miranda; Hiba Najjar; Francisco Alejandro Mena; Jayanth Siddamsetty; Diego Arenas; Michaela Vollmer; Marcela Charfuelan; et al. (IGARSS, 2023)

A Comparative Assessment of Multi-View Fusion Learning For Crop Classification. - Francisco Alejandro Mena; Diego Arenas; Marlon Nuske; Andreas Dengel 001 (IGARSS, 2023)

Feature Attribution Methods for Multivariate Time-Series Explainability in Remote Sensing. - Hiba Najjar; Patrick Helber; Benjamin Bischke; Peter Habelitz; Cristhian Sanchez; Francisco Alejandro Mena; Miro Miranda; Deepak Pathak; Jayanth Siddamsetty; Diego Arenas; Michaela Vollmer; Marcela Charfuelan; et al. (IGARSS, 2023)

Predicting Crop Yield with Machine Learning: An Extensive Analysis of Input Modalities and Models on a Field and Sub-Field Level. - Deepak Pathak; Miro Miranda; Francisco Alejandro Mena; Cristhian Sanchez; Patrick Helber; Benjamin Bischke; Peter Habelitz; Hiba Najjar; Jayanth Siddamsetty; Diego Arenas; Michaela Vollmer; Marcela Charfuelan; et al. (IGARSS, 2023)

Influence of Data Cleaning Techniques on Sub-Field Yield Predictions. - Cristhian Sanchez; Deepak Pathak; Miro Miranda; Marcela Charfuelan; Patrick Helber; Marlon Nuske; Benjamin Bischke; Peter Habelitz; Nafisur Rahman; Francisco Alejandro Mena; Hiba Najjar; Jayanth Siddamsetty; et al. (IGARSS, 2023)

Common Practices and Taxonomy in Deep Multi-view Fusion for Remote Sensing Applications. - Francisco Alejandro Mena; Diego Arenas; Marlon Nuske; Andreas Dengel 001 (CoRR, 2023)

Impact Assessment of Missing Data in Model Predictions for Earth Observation Applications. - Francisco Alejandro Mena; Diego Arenas; Marcela Charfuelan; Marlon Nuske; Andreas Dengel 001 (IGARSS, 2024)

Adaptive Fusion of Multi-view Remote Sensing data for Optimal Sub-field Crop Yield Prediction. - Francisco Alejandro Mena; Deepak Pathak; Hiba Najjar; Cristhian Sanchez; Patrick Helber; Benjamin Bischke; Peter Habelitz; Miro Miranda; Jayanth Siddamsetty; Marlon Nuske; Marcela Charfuelan; Diego Arenas; et al. (CoRR, 2024)

In the Search for Optimal Multi-view Learning Models for Crop Classification with Global Remote Sensing Data. - Francisco Alejandro Mena; Diego Arenas; Andreas Dengel 001 (CoRR, 2024)

Increasing the Robustness of Model Predictions to Missing Sensors in Earth Observation. - Francisco Alejandro Mena; Diego Arenas; Andreas Dengel 001 (CoRR, 2024)

Common Practices and Taxonomy in Deep Multiview Fusion for Remote Sensing Applications. - Francisco Alejandro Mena; Diego Arenas; Marlon Nuske; Andreas Dengel 001 (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2024)

i-QLS: Quantum-Supported Algorithm for Least Squares Optimization in Non-linear Regression. - Supreeth Mysore Venkatesh; Antonio Macaluso; Diego Arenas; Matthias Klusch; Andreas Dengel 001 (ICCS (2), 2025)

Missing data as augmentation in the Earth Observation domain: A multi-view learning approach. - Francisco Alejandro Mena; Diego Arenas; Andreas Dengel 001 (Neurocomputing, 2025)

On What Depends the Robustness of Multi-source Models to Missing Data in Earth Observation? - Francisco Alejandro Mena; Diego Arenas; Miro Miranda; Andreas Dengel 001 (CoRR, 2025)