jen jaewon park
@jaewonp.bsky.social
🌱interests in adaptive memory, memory competition
first yr cog psych phd student @ uc berkeley ʕ •ᴥ•ʔ aly lab
previously postbacc research @ stanford wagner lab & mormino lab
🍒 https://www.alylab.org/
🍒 https://jenjennn23.github.io/
first yr cog psych phd student @ uc berkeley ʕ •ᴥ•ʔ aly lab
previously postbacc research @ stanford wagner lab & mormino lab
🍒 https://www.alylab.org/
🍒 https://jenjennn23.github.io/
Reposted by jen jaewon park
It essentially asks: how much of cognitive neuroscience can be formalized through the lens of Bayesian decision theory? (Answer: a lot)
The book tries to take Marr's levels seriously, showing how computational, algorithmic, and neural levels fit together.
The book tries to take Marr's levels seriously, showing how computational, algorithmic, and neural levels fit together.
January 9, 2026 at 1:27 AM
It essentially asks: how much of cognitive neuroscience can be formalized through the lens of Bayesian decision theory? (Answer: a lot)
The book tries to take Marr's levels seriously, showing how computational, algorithmic, and neural levels fit together.
The book tries to take Marr's levels seriously, showing how computational, algorithmic, and neural levels fit together.