However, most existing neural networks capable of generating complex dynamics are continuous-time models with high dimensionality, resulting in significant resource overhead for digital implementation ...

However, the dependence on initial conditions has not been comprehensively discussed in the literature. This work presents an electrical-synapse-coupled model consisting of two homogeneous Hopfield ...

Associate Professor, Physics, CWRU; Associate Director, Center for AI in Disease Biology, CWRU ...

Spiking neural networks (SNNs) offer a promising energy-efficient alternative to artificial neural networks (ANNs), in virtue of their high biological plausibility, rich spatial-temporal dynamics, and ...

Two trailblazing computer scientists have won the 2024 Turing Award for their work in reinforcement learning, a discipline in ...

A PyG re-implementation of NBFNet can be found here. You may install the dependencies via either conda or pip. Generally, NBFNet works with Python 3.7/3.8 and PyTorch ...