4 papers
CausationEntropy: Pythonic Optimal Causation Entropy
Kevin Slote, Jeremie Fish, Erik Bollt
Optimal Causation Entropy (oCSE) is a robust causal network modeling technique that reveals causal networks from dynamical systems and coupled oscillators, distinguishing direct fr…
On the emergence of numerical instabilities in Next Generation Reservoir Computing
Edmilson Roque dos Santos, Erik Bollt
Next Generation Reservoir Computing (NGRC) is a low-cost machine learning method for forecasting chaotic time series from data. Computational efficiency is crucial for scalable res…
Locality Blended Next Generation Reservoir Computing For Attention Accuracy
Daniel J. Gauthier, Andrew Pomerance, Erik Bollt
We extend an advanced variation of a machine learning algorithm, next-generation reservoir Computing (NGRC), to forecast the dynamics of the Ikeda map of a chaotic laser. The machi…
Fractal Conditional Correlation Dimension Infers Complex Causal Networks
Özge Canlı Usta, Erik M. Bollt
Determining causal inference has become popular in physical and engineering applications. While the problem has immense challenges, it provides a way to model the complex networks…