The same strange ingredient that might stitch together spacetime could also be humming inside your head. Physicists and neuroscientists are increasingly flirting with the idea that the universe and ...

Neural circuits in the brain are highly sophisticated biological systems, orchestrating ultra-fast, parallel computations ...

Something extraordinary has happened, even if we haven’t fully realized it yet: algorithms are now capable of solving ...

RIT alumnus Adam Giammarese received the Edward N. Lorenz Early Career Award for his Ph.D. research in chaos theory and ...

Dr. Leonardos Gkouvelis, researcher at LMU's University Observatory Munich and member of the ORIGINS Excellence Cluster, has ...

AI-native air interfaces represent a shift from mathematical models to learned representations at the PHY layer.

Abstract: Model Predictive Control (MPC) is a promising method for flight control, offering precise stabilization and maneuvering by predicting system behavior using a model of the aircraft dynamics.

Google's Genie generates infinite interactive worlds from text. The secret? AI models compress reality's rules into ...

Intrinsic neural attractors and extrinsic environmental inputs jointly steer the dynamic trajectories of brain activity ...

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known ...

Abstract: This research discovers the ability on using Physics-Informed Neural Network (PINN) for modelling friction force. The training data is generated using the Runge-Kutta method, and the ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...