Photo Credit: University of Tennessee Tickle College of Engineering Communications
Sunny talks to Dr Katie Schuman of the University of Tennessee about the advantages of evolutionary approaches in neural processing. Until the last couple of years, Katie worked at Oak Ridge National Laboratory focusing on evolutionary optimization, deep learning, data analytics, and of course, neuromorphic computing. Among many other things, Katie is an organizer of ICONS, the International Conference on Neuromorphic Systems. After the interview, discussion follows with Giulia and Ralph.
Articles and Papers
- Embracing the hairball: An investigation of recurrence in spiking neural networks for control
- Opportunities for neuromorphic computing algorithms and applications
- Evolutionary Optimization for Neuromorphic Systems
- Avoiding excess computation in asynchronous evolutionary algorithms
- Disclosure of a neuromorphic starter kit
From the discussion
- STICK: Spike time interval computational kernel, a framework for general purpose computation using neurons, precise timing, delays, and synchrony
- Optimization methods for spiking neurons and networks
- Meta-learning in neural networks: A survey
- Biological underpinnings for lifelong learning machines
- NeuroPAC> Accelerating Research on Neuromorphic Perception, Action, and Cognition: Software and Tools
Episode Credits
Producer/Writer: Sunny Bains
Co-hosts: Sunny Bains and Giulia D’Angelo
Editor: Rose Gotto
Audio Production: Taylor Marvin, Coupe Studios Music and Sound Design
Music: 3 of Diamonds by Matt Harris
For EETimes.com
This episode is produced in conjunction with EETimes. Podcast reproduced with permission.
