New ep! 🚨
In Part I of this 2-part episode, Jenny & Deon discuss connectionist modeling, developmental change, developmental tasks, one-hot vs. distributed representations, the give-N task, Bayesian models, Marr’s levels, & more. Stay tuned for Part II!
itsinnate.fireside.fm/38
NEW EPISODE 🚨
Part II is here! Jenny & Deon continue their discussion of Bayesian models and number cognition, including how Lee and Sarnecka used the same Bayesian model to test two competing theories of how children acquire number knowledge.
itsinnate.fireside.fm/39
In case you missed our latest episode, check it out below!
Additional topics discussed:
• the strengths & weaknesses of large vs. small neural networks
• why small models still matter for theory development
• what a connectionist model of the give-N task might look like
• the role of realism in computational modeling
If you're at all interest in computational modeling and number development, this will be the episode for you!
We are SO excited to chat with Dr. Shari Liu (@shariliu.bsky.social) about her scientific journey and, most importantly, about her recent Nature Reviews paper entitled "How physical information is used to make sense of the psychological world"!
The fun continues! In an upcoming episode, Jenny and Deon discuss connectionist modeling, then dive into Lee & Sarnecka (2010), their Bayesian model of the give-N task, and what a more mechanistically-oriented (in Marr's algorithm sense) connectionist version might look like
