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Found 5 papers, 1 papers with code
Categorical Deep Learning: An Algebraic Theory of Architectures
We present our position on the elusive quest for a general-purpose framework for specifying and studying deep learning architectures.
Asynchronous Algorithmic Alignment with Cocycles
In this work, we explicitly separate the concepts of node state update and message function invocation.
A Generalist Neural Algorithmic Learner
The cornerstone of neural algorithmic reasoning is the ability to solve algorithmic tasks, especially in a way that generalises out of distribution.
Graph Neural Networks are Dynamic Programmers
Recent advances in neural algorithmic reasoning with graph neural networks (GNNs) are propped up by the notion of algorithmic alignment.
Imitating Interactive Intelligence
These evaluations convincingly demonstrate that interactive training and auxiliary losses improve agent behaviour beyond what is achieved by supervised learning of actions alone.
