3 papers
nlin.CD2026
From Basins to safe sets: a machine learning perspective on chaotic dynamics
David Valle, Alexandre Wagemakers, Miguel A. F. Sanjuán
The study of chaos has long relied on computationally intensive methods to quantify unpredictability and design control strategies. Recent advances in machine learning, from convol…
nlin.CD2025
AI-Driven Control of Chaos: A Transformer-Based Approach for Dynamical Systems
David Valle, Rubén Capeáns, Alexandre Wagemakers +1
Chaotic behavior in dynamical systems poses a significant challenge in trajectory control, traditionally relying on computationally intensive physical models. We present a machine…
nlin.CD2025
Controlling Transient Chaos in the Lorenz System with Machine Learning
David Valle, Rubén Capeans, Alexandre Wagemakers +1
This paper presents a novel approach to sustain transient chaos in the Lorenz system through the estimation of safety functions using a transformer-based model. Unlike classical me…