Fuzzy neural networks and systems represent a synergistic integration of fuzzy logic and artificial neural networks, aiming to encapsulate human-like reasoning within powerful learning frameworks. By ...

To enable more accurate estimation of connectivity, we propose a data-driven and theoretically grounded framework for optimally designing perturbation inputs, based on formulating the neural model as ...

New research suggests Intelligence may emerge from how the brain’s networks work together rather than a single “intelligence ...

Researchers have unveiled a new generation of photonic computing chips capable of performing real‑time learning and decision‑making using only light-based processes. Photonic chips deliver real‑time ...

Researchers have built new photonic computing chips that allow neural networks to learn using ...

More engineers are turning to reinforcement learning to incorporate adaptive and self-tuning control into industrial systems. It aims to strike a balance between traditional ...

Researchers have developed photonic computing chips that overcome key limitations for a type of neural network known as a photonic spiking neural system. By enabling fast learning and decision making ...

Abstract: Strategic behavior in complex systems—such as digital platforms or autonomous agent networks—is shaped by how information is collected, shared, and used in decision-making. In this talk, I ...

Utilities worldwide are turning to artificial intelligence (AI) and machine learning to stabilize networks, forecast ...

Compared to other regression techniques, a well-tuned neural network regression system can produce the most accurate prediction model, says Dr. James McCaffrey of Microsoft Research in presenting this ...