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A recurrent neural network-based framework to non-linearly model behaviorally relevant neural dynamics

A key objective of several neuroscience studies is to understand and model how the dynamics of distinct populations of neurons give rise to specific human and animal behaviors. Many existing methods ...
San Francisco Fed

Estimating Nonlinear Heterogeneous Agent Models with Neural Networks

We leverage recent advancements in machine learning to develop an integrated method to solve globally and estimate models featuring agent heterogeneity, nonlinear constraints, and aggregate ...