A misconception is currently thriving in the industry that one can become a Generative AI expert without learning ...

Learn how ML-based anomaly detection stops metadata exfiltration in post-quantum AI environments and secures MCP infrastructure against advanced threats.

This valuable study presents a plastic recurrent spiking network model that spontaneously generates repeating neuronal sequences under unstructured inputs. The authors provide solid evidence that, ...

Abstract: Recurrent neural network (RNN) is a neurodynamic method designed to tackle time-varying problems in various technical domains, which are widely derived from scientific research and practical ...

ABSTRACT: Machine learning (ML) has become an increasingly central component of high-energy physics (HEP), providing computational frameworks to address the growing complexity of theoretical ...

This valuable study uses mathematical modeling and analysis to address the question of how neural circuits generate distinct low-dimensional, sequential neural dynamics that can change on fast, ...

A collaboration between SISSA’s Physics and Neuroscience groups has taken a step forward in understanding how memories are stored and retrieved in the brain. The study, recently published in Neuron, ...

The global energy sector is undergoing a transformation, with the electric grid expanding to accommodate an increasing number of assets, including solar arrays, wind farms, batteries, electric ...

Abstract: Large deformation and rotation are nonlinearly coupled in the motion of a flexible deployable system. The deployment trajectory of a flexible deployable system is hard to solve efficiently, ...