POSSM combines the real-time inference of an RNN with the tokenization, pretraining, and finetuning abilities of a Transformer!
Using POYO-style tokenization, we encode spikes in 50ms windows and stream them to a recurrent model (e.g., Mamba, GRU) for fast, frequent predictions over time.
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