This work establishes a valuable theoretical finding about how the spike timing dependence of inhibitory plasticity shapes recurrent network connectivity. The combination of theoretical analysis and ...
This study bridges classical time-series econometrics with modern machine learning by establishing theoretical performance guarantees for recurrent neural networks (RNNs) applied to complex ...