Quanying Liu
@QuanyingL
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Assistant professor @SUSTechSZ; postdoc @caltech; PhD @NCMLabETH @ETH_en Working on AI for brain science, control for neuromodulation, neural data processing
Shenzhen, China
Joined June 2018
AI as a surrogate brain! It enables experiments that are otherwise impossible to perform on the human brain!
Neural Perturbational Inference from the lab of @QuanyingL is an approach for estimating effective connectivity, in which virtual perturbations to a surrogate brain allow gaining insights into human brain functions. https://t.co/lwbuU29Fi3
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Neural Perturbational Inference from the lab of @QuanyingL is an approach for estimating effective connectivity, in which virtual perturbations to a surrogate brain allow gaining insights into human brain functions. https://t.co/lwbuU29Fi3
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Excited to share our recent work in Nature Methods! We've developed Neural Perturbational Inference (NPI), a data-driven approach that maps causal brain networks by virtually perturbing a surrogate brain model.
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We start our afternoon sessions. Welcome our moderators and panelists !
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It is the right time to discuss the scaling law in AI for science field. See you soon (July 26) in Vienna.
Our workshop @icmlconf 2024 happening next week features an exceptional list of speakers and panelists to discuss different aspects/goals of AI for Science: methodology, interpretability, discovery, and an increasingly discussed one, scaling! Schedule: https://t.co/GtRJEKvsFW
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#IJCAIworkshop ๐ฃCall for papers #CFP Workshop on ๐๐ฎ๐ฆ๐๐ง ๐๐ซ๐๐ข๐ง ๐๐ง๐ ๐๐ซ๐ญ๐ข๐๐ข๐๐ข๐๐ฅ ๐๐ง๐ญ๐๐ฅ๐ฅ๐ข๐ ๐๐ง๐๐ โฐSubmission deadline: 14 May โก๏ธ https://t.co/fhp6YXxF1t
#IJCAI2024 #Research #Innovation @QuanyingL @hadi_hoss
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We call for both full papers and abstracts for HBAI 2024 (IJCAI workshop). https://t.co/U3dQrJIQC1 Full paper: 10 pages (accepted as oral, and published in conference proceedings, indexed by EI) Abstract: 2 pages (accepted as poster)
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A recent Perspective Paper from our lab.
Out in @The_InnovationJ! Promoting interactions between cognitive science and large language models. Qu et al. advocate for promoting interaction between cognitive science and LLMs, delve into challenges and solutions for such cooperation, and offer a perspective on future
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My new course, Generative AI for Everyone, is now available! Learn how Generative AI works, how to use it in professional or personal settings, and how it will affect jobs, businesses and society. This course is accessible to everyone, and assumes no prior coding or AI
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Data and code are available at
github.com
Using vision-language models to decode natural image perception from non-invasive brain recordings. - dongyangli-del/EEG_Image_decode
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A breakthrough in EEG based visual reconstruction! Our latest EEG visual decoding model beats the current SOTA, achieving fMRI-level performance. https://t.co/xMProLrjUA
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We organized a cool IJCAI workshop on Human Brain and Artificial Intelligence!!! Welcome to submit your work to HBAI 2024 (the DDL is May 14, 2024) I will see you in Jeju island in August. #HBAI2024 #IJCAI #AI #neuroscience More details about HBAI 2024: https://t.co/lcDpxS6N2Y
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HBAI 2024, a super cool IJCAI workshop on Human Brain and Artificial Intelligence!!! Welcome to submit your work to HBAI 2024 (submission DDL is May 14, 2024) Let's meet in Jeju island in August. More details about HBAI 2024: https://t.co/dzSfnXPx0v
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Actually, 80% of time doing research, 20% of time worrying about research and feeling hopeless...
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Very nice workshop with Both mathematical models and hand on tutorials. Glad to meet the old friends and new friends here.
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