Developing accurate numerical methods for strongly interacting fermions is crucial for improving our understanding of various quantum many-body phenomena, especially unconventional superconductivity.

Cell sorting, essential for diagnostics and early intervention, has evolved from conventional methods to sophisticated microfluidic approaches. These miniaturized systems leverage precise hydrodynamic ...

Which learning goals must individual computational elements pursue to contribute to a network-level task solution? This local understanding is missing in both biological, but also artificial neural ...

Regression analysis is a fundamental concept in the field of machine learning. It falls under supervised learning wherein the algorithm is trained with both input features and output labels. It helps ...

Brain-inspired computing has become an emerging field, where a growing number of works focus on developing algorithms that bring machine learning closer to human brains at the functional level. As one ...

PyMC is a probabilistic programming library for Python that provides tools for constructing and fitting Bayesian models. It offers an intuitive, readable syntax that is close to the natural syntax ...

In 1957, Rosenblatt published pioneering work on the first machine learning algorithm for artificial neurons, known as the perceptron. He helped revolutionize the field of artificial intelligence ...

In this project it is used a Machine Learning model based on a method called Extreme Learning, with the employment of L2-regularization. In particular, a comparison was carried out between: (A1) which ...