ari ☀️
@khoudary.bsky.social
phd researcher in cognitive sciences @ uc irvine. working on evidence accumulation, metacognition, memory, and philosophy of cognitive [neuro]science 🧠 they/them 🏳️🌈 ⚧️ 🇸🇾 https://arikhoudary.com/
it really was such a special time :,) i particularly enjoyed playing “spot the danielle” as she moved from session to session to capture all the mems, which made me v grateful to get this meta-photograph of @okaydaniellle.bsky.social photographing @jackiesullivan.bsky.social’s excellent talk 📸🤳🧠
May 23, 2025 at 12:37 AM
it really was such a special time :,) i particularly enjoyed playing “spot the danielle” as she moved from session to session to capture all the mems, which made me v grateful to get this meta-photograph of @okaydaniellle.bsky.social photographing @jackiesullivan.bsky.social’s excellent talk 📸🤳🧠
with our 🧰 now stocked, we turn to addressing a storied (and stalemated) debate in the evidence accumulation literature: whether decision thresholds remain constant or change over the course of a decision (ie, the "collapsing bounds" debate)
both explain targets really well. but which one is right?
both explain targets really well. but which one is right?
May 20, 2025 at 11:00 PM
with our 🧰 now stocked, we turn to addressing a storied (and stalemated) debate in the evidence accumulation literature: whether decision thresholds remain constant or change over the course of a decision (ie, the "collapsing bounds" debate)
both explain targets really well. but which one is right?
both explain targets really well. but which one is right?
at its heart, the toolkit is designed to unpack what's meant by this famous quotation --
what makes all models wrong? and how do we decide which ones are useful?
well, as it turns out, the same property of models that makes them "wrong" (or better: false) is precisely that which makes them useful!
what makes all models wrong? and how do we decide which ones are useful?
well, as it turns out, the same property of models that makes them "wrong" (or better: false) is precisely that which makes them useful!
May 20, 2025 at 11:00 PM
at its heart, the toolkit is designed to unpack what's meant by this famous quotation --
what makes all models wrong? and how do we decide which ones are useful?
well, as it turns out, the same property of models that makes them "wrong" (or better: false) is precisely that which makes them useful!
what makes all models wrong? and how do we decide which ones are useful?
well, as it turns out, the same property of models that makes them "wrong" (or better: false) is precisely that which makes them useful!