Unification of Symmetries Inside Neural Networks: Transformer,
Feedforward and Neural ODE
Unification of Symmetries Inside Neural Networks: Transformer,
Feedforward and Neural ODE
Understanding the inner workings of neural networks, including transformers, remains one of the most challenging puzzles in machine learning. This study introduces a novel approach by applying the principles of gauge symmetries, a key concept in physics, to neural network architectures. By regarding model functions as physical observables, we find …