Neural Network Model

Neural network models are computational systems inspired by the structure and function of the brain, aiming to solve complex problems through learning from data. Current research focuses on improving model interpretability (e.g., through decompilation and analysis of network weights), enhancing efficiency (e.g., via pruning and coded inference), and addressing challenges in data scarcity and security (e.g., through generative models and encrypted training). These advancements are driving progress in diverse fields, from astrophysics and materials science to finance and healthcare, by enabling more accurate predictions, efficient computations, and improved decision-making.