Meta-Learning Intelligence in Recurrent Graph Neural Networks
Project Manager: Yegor Kuznetsov
- Contact: firstname.lastname@example.org
Recent work has shown recurrent GNNs capable of learning many graph algorithms. However, it’s easy to think of learning itself as a graph algorithm (i.e. backprop operates on computational graphs, and neural networks are structured as graphs) so our project aims to optimize a viable learning algorithm into a GRNN. In essence, we want to directly optimize for Chollet’s definition of intelligence.
We’re optimizing a graph for intelligence.