5 papers
DAW: Dynamics-Aware Weighting for Deep Learning Forecasts of Chaotic Systems
Zhou Fang, Gianmarco Mengaldo
Deep learning surrogates for forecasting chaotic dynamical systems suffer from catastrophic error accumulation over long-term autoregressive rollouts. This behavior is partly tied…
Explainable AI: Learning from the Learners
Ricardo Vinuesa, Steven L. Brunton, Gianmarco Mengaldo
Artificial intelligence now outperforms humans in several scientific and engineering tasks, yet its internal representations often remain opaque. In this Perspective, we argue that…
AI4X Roadmap: Artificial Intelligence for the advancement of scientific pursuit and its future directions
Stephen G. Dale, Nikita Kazeev, Alastair J. A. Price +65
Artificial intelligence and machine learning are reshaping how we approach scientific discovery, not by replacing established methods but by extending what researchers can probe, p…
Dynamical errors in machine learning forecasts
Zhou Fang, Gianmarco Mengaldo
In machine learning forecasting, standard error metrics such as mean absolute error (MAE) and mean squared error (MSE) quantify discrepancies between predictions and target values.…
Explain the Black Box for the Sake of Science: the Scientific Method in the Era of Generative Artificial Intelligence
Gianmarco Mengaldo
The scientific method is the cornerstone of human progress across all branches of the natural and applied sciences, from understanding the human body to explaining how the universe…