Variational Learning Finds Flatter Solutions at the Edge of Stability

Recent advancements in Variational Learning (VL) are shedding light on its effectiveness in training deep neural networks. By exploring the Edge of Stability (EoS) framework, researchers are beginning to understand the implicit regularization that contributes to VL's success. This is significant because it not only enhances our theoretical understanding but also has practical implications for improving machine learning models, making them more efficient and robust.