Abstract: Conventional energy-based methods struggle to determine the origin of Forced Oscillations (FOs) in renewable-rich systems because of their dependency on Dissipating Energy Flow (DEF) ...

DeepFlow is a user-friendly framework for solving PDEs, with a focus on fluid dynamics including the Navier–Stokes equations, using Physics-Informed Neural Networks (PINNs). It provides a ...

Free boundary problems, such as modelling glacier melt, are difficult to capture with neural operators. A new framework addresses this challenge by leveraging the mathematical principle of topological ...

A cybersecurity researcher says Anthropic has silently patched a vulnerability that would have allowed an attacker to bypass the Claude Code network sandbox, potentially enabling data exfiltration.

I recently completed CS50’s Introduction to Artificial Intelligence with Python, a course that offers a broad introduction to core AI concepts while also giving students the chance to build practical ...

To ensure the safety of industrial systems and reduce downtimes, fault diagnosis must be accurate and timely. A graph neural network-based method introduced in this paper is referred to as the ...

Abstract: Recent advances in machine learning have begun to embed oscillatory network principles within neural architectures, aiming to enhance computational efficiency and robustness in time-series ...

@article{zini2026alzheimer, title={Alzheimer’s disease classification from EEG using a multiscale temporal deep network}, author={Zini, Simone and Barbera, Thomas and Bianco, Simone and Napoletano, ...