Academic record
A cumulative archive of peer-reviewed journal articles on reliable model selection, graph learning and environmental forecasting.
Author identity: Marc Semper Lloret publishes scientific work as Marc Semper. Journal record reviewed 29 July 2026.
Knowledge-Based Systems, article 116673, 2026
Choosing the best forecasting model from one clean validation set can produce a fragile deployment decision. This work tests whether that decision survives realistic changes to the evaluation reference and turns the diagnosis into an auditable recommendation.
Mathematics, vol. 14, no. 5, article 908, 2026
This study asks whether a graph forecasting model can learn better node representations by training across several related datasets instead of learning every representation from scratch.
International Journal of Environmental Science and Technology, vol. 23, no. 1, article 69, 2026
The work models how atmospheric aerosols evolve across the planet by combining a global graph of observations with temporal patterns at several scales.
International Journal of Environmental Science and Technology, vol. 23, no. 1, article 63, 2026
Air quality at one monitoring station is connected to conditions elsewhere. This work learns both nearby and long-range relationships across the Spanish monitoring network.
Applied Sciences, vol. 15, no. 10, article 5576, 2025
Urban noise has both a temporal rhythm and a spatial structure. The study compares deep-learning approaches that represent those two dimensions explicitly across Madrid.
Journal of Environmental Management, vol. 371, article 122922, 2024
This research tests deep-learning strategies for forecasting global carbon dioxide and methane concentrations six months ahead from satellite and environmental data.
Reproducible citation
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