arxiv preprint – VanillaNet: the Power of Minimalism in Deep Learning

In this episode we discuss VanillaNet: the Power of Minimalism in Deep Learning
by Hanting Chen, Yunhe Wang, Jianyuan Guo, Dacheng Tao. The paper introduces VanillaNet, a neural network architecture that prioritizes simplicity and minimalism. It avoids complex operations like self-attention and uses compact and straightforward layers. Experimental results demonstrate that VanillaNet performs comparably to existing deep neural networks and vision transformers, indicating the potential of minimalism in deep learning.