Track how discrete representations evolve during neural network training — lifecycle events, phase transitions, ontology discovery, and causal verification
pythonmachine-learningpytorchneural-networksrepresentation-learningcausal-inferencesparse-autoencodersinterpretabilityfsqvq-vaetraining-dynamicsphase-transitionsdiscrete-representationsmechanistic-interpretabilitylifecycle-tracking
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Updated
Jul 21, 2026 - Python