Extreme events gain the attention of researchers due to their utmost importance in various
contexts ranging from climate to brain. An observable that deviates significantly from its long …

The superconducting Josephson junction shows spiking and bursting behaviors, which have
similarities with neuronal spiking and bursting. This phenomenon had been observed long …

A reservoir computing based echo state network (ESN) is used here for the purpose of
predicting the spread of a disease. The current infection trends of a disease in some …

In the field of complex dynamics, multistable attractors have been gaining significant
attention due to their unpredictability in occurrence and extreme sensitivity to initial …

The remarkable flexibility and adaptability of both deep learning models and ensemble
methods have led to the proliferation for their application in understanding many physical …

Reservoir computing offers a great computational framework where a physical system can
directly be used as computational substrate. Typically a “reservoir” is comprised of a large …

Reservoir computing, a new method of machine learning, has recently been used to predict
the state evolution of various chaotic dynamic systems. It has significant advantages in terms …

One must be aware of the black-box problem by applying machine learning models to
analyze high-dimensional neuroimaging data. It is due to a lack of understanding of the …

It is generally known that in a mixture of coupled active and inactive nonlinear oscillators, the
entire system may stop oscillating and become inactive if the fraction of active oscillators is …

Machine learning techniques have been witnessing perpetual success in predicting and
understanding behaviors of a diverse range of complex systems. By employing a deep …