3 papers
cs.NE2025
Reservoir Computation with Networks of Differentiating Neuron Ring Oscillators
Alexander Yeung, Peter DelMastro, Arjun Karuvally +3
Reservoir Computing is a machine learning approach that uses the rich repertoire of complex system dynamics for function approximation. Current approaches to reservoir computing us…
cs.NE2025
Transient Dynamics in Lattices of Differentiating Ring Oscillators
Peter DelMastro, Arjun Karuvally, Hananel Hazan +2
Recurrent neural networks (RNNs) are machine learning models widely used for learning temporal relationships. Current state-of-the-art RNNs use integrating or spiking neurons -- tw…
cs.NE2022
Temporal Weights
Adam Kohan, Ed Rietman, Hava Siegelmann
In artificial neural networks, weights are a static representation of synapses. However, synapses are not static, they have their own interacting dynamics over time. To instill wei…