no code implementations • 29 Sep 2017 • Georgios Detorakis, Sadique Sheik, Charles Augustine, Somnath Paul, Bruno U. Pedroni, Nikil Dutt, Jeffrey Krichmar, Gert Cauwenberghs, Emre Neftci
Embedded, continual learning for autonomous and adaptive behavior is a key application of neuromorphic hardware.
no code implementations • 5 Jan 2017 • Sadique Sheik, Somnath Paul, Charles Augustine, Gert Cauwenberghs
Several learning rules for synaptic plasticity, that depend on either spike timing or internal state variables, have been proposed in the past imparting varying computational capabilities to Spiking Neural Networks.
1 code implementation • 16 Dec 2016 • Emre Neftci, Charles Augustine, Somnath Paul, Georgios Detorakis
Building on these results, we demonstrate an event-driven random BP (eRBP) rule that uses an error-modulated synaptic plasticity for learning deep representations in neuromorphic computing hardware.
no code implementations • 11 Jul 2016 • Bruno U. Pedroni, Sadique Sheik, Siddharth Joshi, Georgios Detorakis, Somnath Paul, Charles Augustine, Emre Neftci, Gert Cauwenberghs
We present a novel method for realizing both causal and acausal weight updates using only forward lookup access of the synaptic connectivity table, permitting memory-efficient implementation.