A deep network is best understood in terms of components used to design it—objective functions, architecture and learning rules—rather than unit-by-unit computation. Richards et al. argue that this inspires fruitful approaches to systems neuroscience.
- Blake A. Richards
- Timothy P. Lillicrap
- Konrad P. Kording
