I am aware that back-propagation through time is used for training the recurrent neural network. But I am not able to understand how this happens for the bi-directional versions of the recurrent neural networks?
So, I was hoping if anyone help me with:
- Understanding with an example the training of bi-directional recurrent neural networks using back-propagation through time? (I tried following the original paper https://ieeexplore.ieee.org/document/650093, but it was kind of confusing for me when they perform the backward pass for training)