A Gentle Introduction to Graph Neural Networks
What components are needed for building learning algorithms that leverage the structure and properties of graphs?
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Understanding Convolutions on Graphs
Understanding the building blocks and design choices of graph neural networks.
Distill Hiatus
After five years, Distill will be taking a break.
Adversarial Reprogramming of Neural Cellular Automata
Reprogramming Neural CA to exhibit novel behaviour, using adversarial attacks.
Weight Banding
Weights in the final layer of common visual models appear as horizontal bands. We investigate how and why.
Branch Specialization
When a neural network layer is divided into multiple branches, neurons self-organize into coherent groupings.
Multimodal Neurons in Artificial Neural Networks
We report the existence of multimodal neurons in artificial neural networks, similar to those found in the human brain.
Self-Organising Textures
Neural Cellular Automata learn to generate textures, exhibiting surprising properties.
Visualizing Weights
We present techniques for visualizing, contextualizing, and understanding neural network weights.
Curve Circuits
Reverse engineering the curve detection algorithm from InceptionV1 and reimplementing it from scratch.