Reservoir computing originates in the early 2000s, the core idea being to utilize dynamical
systems as reservoirs (nonlinear generalizations of standard bases) to adaptively learn …

Abstract Long Short-Term Memory (LSTM) is a popular Recurrent Neural Network (RNN)
algorithm known for its ability to effectively analyze and process sequential data with long …

Neural networks have been successfully employed in various domains such as
classification, regression and clustering, etc. Generally, the back propagation (BP) based …

The rapid development and open-source release of highly performant computer vision
models offers new potential for examining how different inductive biases impact …

The rapid release of high-performing computer vision models offers new potential to study
the impact of different inductive biases on the emergent brain alignment of learned …

Ever-growing demand for artificial intelligence has motivated research on unconventional
computation based on physical devices. While such computation devices mimic brain …

We introduce a probability distribution, combined with an efficient sampling algorithm, for
weights and biases of fully-connected neural networks. In a supervised learning context, no …

Problems For people all over the world, cancer is one of the most feared diseases. Cancer is
one of the major obstacles to improving life expectancy in countries around the world and …

In recent years, advancements in machine learning (ML) techniques, in particular, deep
learning (DL) methods have gained a lot of momentum in solving inverse imaging problems …

Our decisions often depend on multiple sensory experiences separated by time delays. The
brain can remember these experiences and, simultaneously, estimate the timing between …