A Gentle Introduction to Graph Neural Networks
What components are needed for building learning algorithms that leverage the structure and properties of graphs?
What components are needed for building learning algorithms that leverage the structure and properties of graphs?
Understanding the building blocks and design choices of graph neural networks.
Reprogramming Neural CA to exhibit novel behaviour, using adversarial attacks.
Weights in the final layer of common visual models appear as horizontal bands. We investigate how and why.
When a neural network layer is divided into multiple branches, neurons self-organize into coherent groupings.
We report the existence of multimodal neurons in artificial neural networks, similar to those found in the human brain.
Neural Cellular Automata learn to generate textures, exhibiting surprising properties.
We present techniques for visualizing, contextualizing, and understanding neural network weights.
Reverse engineering the curve detection algorithm from InceptionV1 and reimplementing it from scratch.