Yao Qin
@YaoQin_UCSB
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Assistant Professor @UCSB; Research Scientist @Google DeepMind; PhD @UCSD
Santa Barbara, CA
Joined November 2015
Kenan has lead this amazing work for precise, iterative and customizable image editing. Go to our paper or website: to learn more about it! 😃.
Excited to introduce SPICE, a novel image editing framework that supports precise and local editing. In the example shown below, we iteratively edit the area around a fridge for various tasks. Paper: Code:
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RT @ninamiolane: The era of artificial scientific intelligence is here. As algorithms generate discoveries at scale, what role remains for….
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Glad to share this work to build connections between these two research areas! Full paper is available at:
🧵New survey: Bridging Distribution Shift and AI Safety. Distribution shift and AI safety have long been studied in parallel. But how can their insights formally inform each other?. We present the first comprehensive, mathematically grounded, and one-to-one aligned treatment. 1/6.
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Great work by Litian on this Neural Collapse inspired OOD detection work, accepted at CVPR-25! Code is also available at: Try out to see how Neural Collapse helps robustness!.
Our #CVPR2025 paper is out!.Inspired by Neural Collapse, we show that OOD samples lie far from the origin and class weights—tying together many prior methods. Huge thanks to @YaoQin_UCSB, @liuziwei7, and @JingkangY for the collaboration & OpenOOD support! .
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🚨Only 1 day to go! 🚨.Join us at AIM-FM: Advancements In Medical Foundation Models workshop at NeurIPS 2024!.📅 When: December 14th, 2024, 8:20 a.m. PST.📍 Where: East Ballroom A, B. We will be exploring the transformative potential of Medical Foundation Models (MFMs) in smart
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RT @ninamiolane: Can't believe it's a year already! Incredibly proud of what this team has accomplished 🧠🌟 . @emilyjacobs @caitaylo @russpo….
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I'll be at @NeurIPSConf next week and would love to catch up in person! . 🎉My lab at UCSB is hiring PhD students working on AI Safety and AI for Healthcare. If you're passionate about these areas, welcome to apply to UCSB and happy to chat if you're attending NeurIPS!.
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RT @goodfellow_ian: Posting a call for help: does anyone know of a good way to simultaneously treat both POTS and Ménière’s disease? Please….
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Great work and congratulations 👏 @WilliamWangNLP.
🚀Introducing ChipAgents: the World's First AI Agent for Chip Design and Verification. Get ready to supercharge your workflow and accelerate your time-to-market! 💻⚡
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Welcome to submit to our AIM-FM Workshop at NeurIPS 2024 to advance the medical foundation models 😀.
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Join us for this exciting postdoc opportunity and work on AI for science✌️😊.
We are recruiting postdocs for 2024/25 @ai_ucsb ! . You want to build next-gen artificial scientific intelligence?🤖. Apply to the UCSB Real AI Initiative!.Deadline: Sept 15 .Competitive salary.Prime location for your future office 🌊. @YaoQin_UCSB @HaewonJeong00 @UofCalifornia
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RT @goodfellow_ian: If you’re unfamiliar with long COVID, this thread from @SalvMattera about his experiences makes it clear why it’s so im….
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🥰 Super excited to share this new work on benchmarking LLMs for carbohydrate estimation, which is a huge daily burden that every patient with diabetes needs to deal with multiple times every day. 👏👍Proud of my students for starting to investigate the potential of LLMs in.
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Excited to share this new work on degradation in the chain of diffusion done by our amazing students, co-advised with @HaewonJeong00 😊!.
🏞️Ever wondered what happens if we iteratively finetune a diffusion model on its own outputs?.SEVERE DEGRADATION! 🚨.Our latest research uncovers this phenomenon and introduces ReDiFine, a novel approach to ensure sustainability. 📜Preprint: 🧵1/5
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RT @sijialiu17: The 3rd AdvML-Frontiers Workshop (@AdvMLFrontiers is set for #NeurIPS 2024 (@NeurIPSConf)! This ye….
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Litian did this amazing work in designing this efficient and effective OOD detector based on decision boundary 👏👍. Come to talk to us at ICML in Vienna very soon 😉.
Excited to share our #ICML2024 paper! Detect Out-of-Distribution (OOD) samples efficiently and effectively with our detector: OOD samples are closer to decision boundaries, In-Distribution (ID) samples are further away!.
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RT @ucsantabarbara: Haewon Jeong of @ucsbece is addressing bias in machine learning. Supported by a $558,000 @NSF CAREER Award, her innovat….
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Come to talk to my student @andong_1997 and me at CVPR poster #59! .Paper link: .Code is available at:
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