A wind speed forecasting technique, using deep learning architectures based on long short-
term memory (LSTM) model and bidirectional long short-term memory (BiLSTM) model is …

Methods for time series prediction and classification of gene regulatory networks (GRNs)
from gene expression data have been treated separately so far. The recent emergence of …

Chaotic itinerancy is a frequently observed phenomenon in high-dimensional nonlinear
dynamical systems and is characterized by itinerant transitions among multiple quasi …

The aim of this work is to find a good mathematical model for the classification of brain states
during visual perception with a focus on the interpretability of the results. To achieve it, we …

The architecture of communication within the brain, represented by the human connectome,
has gained a paramount role in the neuroscience community. Several features of this …

In a neural network, an autapse is a particular kind of synapse that links a neuron onto itself.
Autapses are almost always not allowed neither in artificial nor in biological neural networks …

Understanding how neural networks process information is a fundamental challenge in
neuroscience and artificial intelligence. A pivotal question in this context is how external …

Disorder is a pervasive characteristic of natural systems, offering a wealth of non-repeating
patterns. In this study, we present a novel storage method that harnesses naturally-occurring …

Free-running recurrent neural networks (RNNs), especially probabilistic models, generate
an ongoing information flux that can be quantified with the mutual information I [x→(t), x→(t+ …

We consider the dynamics of interpersonal relations which leads to balanced states in a fully
connected network. Here this approach is applied to directed networks with asymmetric …