Erdos, explores what researchers call autoformalization, the process of converting traditional mathematical proofs into formats machines can verify using tools such as Lean and Coq.

Facing strict privacy laws, telcos use AI-generated synthetic data as a compliant workaround to train ML models without exposing sensitive customer information.

Abstract: The exponential growth in Internet-connected devices has escalated the demand for optimized network topologies to ensure high performance. Traditional optimization methods often fall short ...

MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the “Company”), a technology service provider, released a core quantum machine learning technology oriented toward sequential learning tasks—the ...

This is the MATLAB code for the implementation of neural pupil engineering FPM (NePE-FPM), an optimization framework for FPM reconstruction for off-axis areas. NePE-FPM engineers the pupil function ...

Stephen Whitelam, a researcher whose work spans thermodynamic theory and machine learning, has described a framework for generating images from pure noise by using the physics of heat and motion ...

Alcohol use disorder (AUD) is a chronic, relapsing condition marked by compulsive drinking, imposing a significant burden on both the individual and their environment. The intrinsic neural timescale ...

Abstract: Physics-informed neural networks (PINNs) provide a flexible framework for solving neutron diffusion equations, yet their accuracy and stability are often hindered by limited spatial ...