High-Low Frequency Detectors
A family of early-vision neurons reacting to directional transitions from high to low spatial frequency.
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Naturally Occurring Equivariance in Neural Networks
Neural networks naturally learn many transformed copies of the same feature, connected by symmetric weights.
Understanding RL Vision
With diverse environments, we can analyze, diagnose and edit deep reinforcement learning models using attribution.
Communicating with Interactive Articles
Examining the design of interactive articles by synthesizing theory from disciplines such as education, journalism, and visualization.
Self-classifying MNIST Digits
Training an end-to-end differentiable, self-organising cellular automata for classifying MNIST digits.
Thread: Differentiable Self-organizing Systems
A collection of articles and comments with the goal of understanding how to design robust and general purpose self-organizing systems.
Curve Detectors
Part one of a three part deep dive into the curve neuron family.
Exploring Bayesian Optimization
How to tune hyperparameters for your machine learning model using Bayesian optimization.
An Overview of Early Vision in InceptionV1
An overview of all the neurons in the first five layers of InceptionV1, organized into a taxonomy of 'neuron groups.'
Visualizing Neural Networks with the Grand Tour
By focusing on linear dimensionality reduction, we show how to visualize many dynamic phenomena in neural networks.