Before revision:  Finally, we develop a field-theory for gradients that arise in training, by incorporating the adjoint sensitivity framework from control theory in the DMFT . This paves the way for the use of powerful field-theoretic techniques to study training / gradients in large RNNs.
After revision:  Finally, we develop a field-theory for gradients that arise in training, by incorporating the adjoint sensitivity framework from control theory with the dynamical mean-field theory . This paves the way for the use of powerful field-theoretic techniques to study training / gradients in large RNNs.