From left to right: Jamie Knight from the University of Sussex, Sebastian Siegel from the Peter Grünberg Institute in Jülich, Laura Kriener from the Institute of Neuroinformatics in Zurich, Chiara Bartolozzi from the Italian Institute of Technology, and Federico Corradi from Eindhoven University of Technology. (Source: University of Sussex).
Five engineers debate neuromorphic sensing and learning. Recorded at the Neuromorphic Hardware and Algorithms conference at the University of Sussex, panelists are Chiara Bartolozzi from the Italian Institute of Technology, Federico Corradi from Eindhoven University of Technology, James Knight from the University of Sussex, Laura Kriener from the Institute of Neuroinformatics in Zurich, and Sebastian Siegel from the Peter Grünberg Institute in Jülich. Sunny chairs, and discussion follows with Giulia and Ralph.
Articles and Papers
- Constraints on the design of neuromorphic circuits set by the properties of neural population codes
- Traces propagation: memory-efficient and scalable forward-only learning in spiking neural networks
- Neuromorphic is dead. Long live neuromorphic.
From the discussion
- Disentangling temporal and rate codes in the primate somatosensory cortex
- Principles of temporal processing across the cortical hierarchy
- Bio-inspired system architecture for energy efficient, BIGDATA computing with application to wide area motion imagery
- Legendre memory units: continuous-time representation in recurrent neural networks
- A dataset of differentiable biologically-derived single neuron models
- Systematic integration of structural and functional data into multi-scale models of mouse primary visual cortex
- Experts weigh impact of Prophesee-Qualcomm deal
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.
