DynamicGate MLP enables concurrent learning and inference by separating gating from representation parameters, so that even asynchronous updates produce outputs equivalent to a valid fixed model snapshot.
Memo: Test time robustness via adapta- tion and augmentation
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Learning Inference Concurrency in DynamicGate MLP Structural and Mathematical Justification
DynamicGate MLP enables concurrent learning and inference by separating gating from representation parameters, so that even asynchronous updates produce outputs equivalent to a valid fixed model snapshot.