Linear Network

Linear networks, a simplified model of neural networks, are a focus of current research aiming to understand fundamental learning dynamics and generalization capabilities. Studies explore various aspects, including the geometry of loss landscapes, generalization bounds for nearly-linear networks, and the emergence of different coding schemes depending on network architecture and data properties. This research provides valuable insights into the behavior of more complex neural networks, offering a tractable framework for theoretical analysis and informing the design of efficient and interpretable models for applications such as zero-shot learning and speech translation.