Track how discrete representations evolve during neural network training — lifecycle events, phase transitions, ontology discovery, and causal verification
python machine-learning pytorch neural-networks representation-learning causal-inference sparse-autoencoders interpretability fsq vq-vae training-dynamics phase-transitions discrete-representations mechanistic-interpretability lifecycle-tracking
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Updated
May 26, 2026 - Python