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This paper has a nice spiking network learning temporal patterns via STDP and IP (intrinsic plasticity). https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003512
I like the three tasks, and I'd be very curious how the LMU/dynamics learning approaches compare to this.
There's also some interesting analysis of the learned representation that might be worth applying to the LMU representation....
The text was updated successfully, but these errors were encountered:
This might also be a good place to look more at the use of BCM in comparison to STDP
Here's another related paper too
https://www.frontiersin.org/articles/10.3389/neuro.10.023.2009/full
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This paper has a nice spiking network learning temporal patterns via STDP and IP (intrinsic plasticity). https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003512
I like the three tasks, and I'd be very curious how the LMU/dynamics learning approaches compare to this.
There's also some interesting analysis of the learned representation that might be worth applying to the LMU representation....
The text was updated successfully, but these errors were encountered: