Reviews: Enabling hyperparameter optimization in sequential autoencoders for spiking neural data

Authors provide novel approaches to calculate cross-validated reconstruction loss by using one of two proposed solutions: Sample validation and Coordinated dropout described above. The ideas are first described with the help of a synthetically generated dataset and experimental results on Monk This paper would be much stronger if the ideas were demonstrated on multiple real datasets. In the current organization, the ideas are first demonstrated on synthetically generated data. It is not clear why the "Monkey J Maze" is not used right from the beginning, instead of spending significant portion of the data in describing the synthetic data generation process. Synthetic data is unconvincing especially in an unsupervised learning setting.