Visualizing Neural Networks with the Grand Tour
By focusing on linear dimensionality reduction, we show how to visualize many dynamic phenomena in neural networks.
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Zoom In: An Introduction to Circuits
By studying the connections between neurons, we can find meaningful algorithms in the weights of neural networks.
Thread: Circuits
What can we learn if we invest heavily in reverse engineering a single neural network?
Growing Neural Cellular Automata
Training an end-to-end differentiable, self-organising cellular automata model of morphogenesis, able to both grow and regenerate specific patterns.
Visualizing the Impact of Feature Attribution Baselines
Exploring the baseline input hyperparameter, and how it impacts interpretations of neural network behavior.
Computing Receptive Fields of Convolutional Neural Networks
Detailed derivations and open-source code to analyze the receptive fields of convnets.