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arturoornelasb / reptimeline

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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
  • Updated May 5, 2026
  • Python

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