Stories

Every story follows the same plan: the finding, the question, the theory in plain words, where it sits on the complexity ladder, an example in figures, what it brings and its limits. Technical details and code are on the methods site.

Compute directly · Hybridize · Learn frugally · AI in its place · Demonstrate trust

Compute directly

When the link is known, compute it with an explicit model, calibrated and validated on data; learning is added only for a demonstrated benefit.

Hybridize

When the model falls short, complete it: keep the model, learn only what is missing.

Learn frugally

When the useful relations are not known well enough, evaluate what the data can teach, with only as much complexity as pays.

Étude MIMO-ELM, figure 1 de la version auteur : mesures et prévisions à une heure pour sept signaux énergétiques corses, environ cent heures en hiver.
Learn frugally · Energy

Seven signals, one ELM

One frugal learner forecasts the whole Corsican electricity mix.

AI in its place

Language models help people use validated tools; the calculation, the checking and the responsibility stay with validated codes and people.

Demonstrate trust

Judge against a reference, publish code, data and limits, make research findable and reusable.

Explore the results

How forecastable is the sun?
Solar forecastability evaluated at 68 weather stations, across ten models and 24 horizons.

Better persistence
An analytical cyclostationary reference that improves on classical persistence on the studied solar series.

Seven signals, one ELM
Seven energy outputs evaluated on six years of hourly data from Corsica.

Beyond pointwise errors
A synthetic experiment shows why small displacements can mislead a pointwise error metric.

When RMSE hides a difference
Two models with the same rounded nRMSE are distinguished by persistence-relative evaluation.

These research stories explain results from papers on which I am first author. Each page includes the question, evidence, interpretation, limitations and full collective attribution, in English and French.

Solar forecasting, made simple

Explore the ideas, methods and evidence, Prévision solaire : faire simple

Forecastability, useful baselines, error evaluation and frugal models: a guided route through our published studies, open code and ongoing research, with full attribution.