Biologically Plausible, Human-scale Knowledge Representation

By Eric Crawford, Matthew Gingerich, Chris Eliasmith. 2016

61 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Marta Garnelo
2. Murray Shanahan
3. Sjoerd van Steenkiste
4. Blai Bonet
5. Alejandro Barredo Arrieta
6. R'obert Csord'as
7. Eric Crawford
8. Anirudh Goyal

Citations in the corpus

• Reconciling deep learning with symbolic artificial intelligence: representing objects and relations (2019, background): “Although various ways to incorporate variables and variable binding in neural networks have been proposed, some biologically inspired (e.g. [43,44]) and some less so (e.g. [45]), to date these have not been integrated with mechanisms for learning symbolic relational representations from raw data.”