5 papers
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…
Basins of Attraction: A Dynamical Zoo
Alexandre Wagemakers
Research in multistable systems is a flourishing field with countless examples and applications across scientific disciplines. I present a catalog of multistable dynamical systems…
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…
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…
Efficient and stable derivative-free Steffensen algorithm for root finding
Alexandre Wagemakers, Vipul Periwal
We explore a family of numerical methods, based on the Steffensen divided difference iterative algorithm, that do not evaluate the derivative of the objective functions. The family…