Yongquan Qu
@yongquan-qu.bsky.social
PhD candidate @Columbia University, Simulation Intelligence Resident @Pasteur Labs&ISI, GRA @leapstc.bsky.social LEAP NSF-STC | SciML for Turbulence and Data Assimilation | Math -> Atmospheric Science https://yongquan-qu.github.io
Don't miss LEAP #Research Updates w/ @yongquan-qu.bsky.social + Jaeyoung Jung! 📅 THIS THURS || 5/8/2025 🕛 12p EST 📍 @columbiaseas.bsky.social Innovation Hub / Zoom 💻 RSVP: www.eventbrite.com/e/1134230346... #LEAPEducation #climate #community #ML #data #AI #atmosphere #ESM @climate.columbia.edu
Meanwhile, @juannat7.bsky.social has Vancouver covered at @neuripsconf.bsky.social w/"ChaosBench: A Multi-Channel, Physics-Based Benchmark for Subseasonal-to-Seasonal Climate Prediction!" Check out the presentation + poster: https://buff.ly/4ff6xAs @neuripsconf.bsky.social #NeurIPS2024
NeurIPS 2024
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TODAY at 14:10p in 154A-B, don't miss this invited presentation: "A43Q-01: Do We Need Parameterizations in the Era of Generative AI?" by @pierregentine.bsky.social w/Joseph Lockwood, Maggie Powell, @yongquan-qu.bsky.social @juannat7.bsky.social + @stephanmandt.bsky.social https://buff.ly/3VxnW0g
Do we need parameterizations in the era of generative AI?
Closures and parameterizations are critical for coarse-resolution Earth system ...
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Find LEAP posters online at #AGU24 iPoster Gallery, 8a-5:30p daily! NG01-06: Deep Generative Data Assimilation in Multimodal Setting (@juannat7.bsky.social) NG01-10: Joint Parameter + Parameterization Inference w/Uncertainty Quantification thru Differentiable Programming (@yongquan-qu.bsky.social)
