Song Mei @Song__Mei
Assistant Professor at UC Berkeley, Department of Statistics and EECS. Researcher working on foundations of AI and deep learning. stat.berkeley.edu/~songmei/ Berkeley, CA Joined January 2015-
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Why do diffusion models use the U-Net architecture? Fascinatingly, the U-Net's encoder-decoder structure with long skip connections naturally encodes the belief propagation algorithm for hierarchical models. Explore more in this paper! arxiv.org/abs/2404.18444. .
Delighted to be launching a Open Source Program Office (OSPO) at @BerkeleyDataSci , housed under @UCBIDS and led by Jarrod Millman, long-time scientific python developer and leader. Huge thanks to @SloanFoundation @epistemographer for their ongoing support for Scientific OSS!
Delighted to be launching a Open Source Program Office (OSPO) at @BerkeleyDataSci , housed under @UCBIDS and led by Jarrod Millman, long-time scientific python developer and leader. Huge thanks to @SloanFoundation @epistemographer for their ongoing support for Scientific OSS!
Our new youTube channel: youtube.com/playlist?list=… Comments welcome!
Check out the ICML workshop on Theoretical Foundations of Foundation Models!
Check out the ICML workshop on Theoretical Foundations of Foundation Models!
My group at Berkeley Stats and EECS has a postdoc opening in the theoretical (e.g., scaling laws, watermark) and empirical aspects (e.g., efficiency, safety, alignment) of LLMs or diffusion models. Send me an email with your CV if interested!
So excited and so very humbled to be stepping in to head AI Safety and Alignment at @GoogleDeepMind. Lots of work ahead, both for present-day issues and for extreme risks in anticipation of capabilities advancing.
So excited and so very humbled to be stepping in to head AI Safety and Alignment at @GoogleDeepMind. Lots of work ahead, both for present-day issues and for extreme risks in anticipation of capabilities advancing.
Thanks to our organizers @XihongLin @tz33cu and to all the panelists @hongtuzhu1 @WenyiWang4 @Hulin_Wu @HaodaFu @bbiinnyyuu .. for their fantastic and inspiring presentations and contributions to forward-looking discussions Thanks for cohosting@StatsUpAI youtube.com/live/iTupgaXHi…
👏 IMS Council has approved the appointment of Hans-Georg Müller and Harrison Zhou as Editors of Annals of Statistics for the term January 1, 2025–December 31, 2027. They will be taking over from co-editors Enno Mammen and Lan Wang. @InstMathStat imstat.org/2024/02/15/inc…
📢 #ICML2024 authors! Help improve ML peer review! 🔬📝 Check your inbox for an email titled "[ICML 2024] Author Survey" and rank your submissions. 🏆📈 Your confidential input is crucial, and won't affect decisions. 🔒✅ Survey link in email or "Author Tasks" on OpenReview.
Join us on a tranquil Spring Sunday morning to discuss Statistics, Machine Learning, Artificial Intelligence, Academic Journals, and Data Science Education with 14 distinguished faculty panelists. 👇👇👇 No registration is needed. #statistics #AI #MachineLearning
My co-author @rlbarter and I are thrilled to announce the online release of our MIT Press book "Veridical Data Science: The Practice of Responsible Data Analysis and Decision Making" (vdsbook.com), an essential source for producing trustworthy data-driven results.
Spiked tensor model has a huge stat/comp gap classically. What happens to quantum algorithms? We show QAOA has the same comp threshold as power iteration, implying such classical hardness also exists in quantum world. arxiv.org/abs/2402.19456 w/ @leologist and Joao Basso
Rethinking diffusion models: We interpret neural networks as denoising 𝗮𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺𝘀, not just 𝗳𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀. This new perspective lets us prove tight error bounds on score estimation in diffusion models with deep networks. More in our paper: arxiv.org/abs/2309.11420
Thrilled to share our work on showing transformers can provably perform in-context learning like a statistician. We presented surprising experimental results and a comprehensive theoretical analysis.
Thrilled to share our work on showing transformers can provably perform in-context learning like a statistician. We presented surprising experimental results and a comprehensive theoretical analysis.
Thrilled to share our new work "Transformers as Statisticians👩🎓👨🎓" Unveiling a new mechanism "In-Context Algorithm Selection" for In-Context Learning (ICL) in LLMs/transformers. ++ A comprehensive theory for transformers to do ICL. arxiv.org/abs/2306.04637 Thread⬇️
I am starting my research blog today. I will discuss about methods from statistical physics and random matrix theory in the first several blogs. Hope you will have fun there! (P.S., this is also my first tweet) meisong541.github.io
Yi Ma @YiMaTweets
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ViktorM🇺🇦 @viktor_m81
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Sreerag M./ ശ്ര.. @sreagm
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Gregory Axler @g_axler
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【𝕐o𝕦𝕤𝕖�.. @YosGPT
10K Followers 5K Following Programming Engineer & Linux+ | IT & Net+ | CCIE & CISSP | Azure Developer & Multi-Clouds Architect+ | Quantum AI Builder+ | #الحمدلله_على_نعمة_الامارات 🇦🇪 ❤️
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4 Followers 55 Following
Arif Ahmad @arif_ahmad_py
273 Followers 7K Following All things AI, Computer Science and Circuits! Prev. @GoogleAI
Clément Canonne @ccanonne_
31K Followers 928 Following Senior Lecturer @Sydney_Uni. Postdocs @IBMResearch, @Stanford; PhD @Columbia. Converts ☕ into puns: sometimes theorems. He/him. @[email protected]
Gautam Kamath @thegautamkamath
44K Followers 507 Following Assistant Prof of CS @UWaterloo, Faculty @VectorInst, Canada @CIFAR_News AI Chair. Co-EiC @TmlrOrg. I lead @TheSalonML. Privacy, robustness, machine learning.
Yi Ma @YiMaTweets
71K Followers 123 Following Chair Professor in AI, Director of IDS, Head of CS, HKU; Professor of EECS, Berkeley; Author of Book: High-Dim Data Analysis, https://t.co/gwaqMJp8av.
Jason Lee @jasondeanlee
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Zhimei Ren @RenZhimei
822 Followers 270 Following Assistant professor @Wharton stats. Former postdoc @UChicago & PhD from @Stanford.
Yann LeCun @ylecun
711K Followers 718 Following Professor at NYU. Chief AI Scientist at Meta. Researcher in AI, Machine Learning, Robotics, etc. ACM Turing Award Laureate.
Kyunghyun Cho @kchonyc
61K Followers 2K Following a combination of a mediocre scientist, a mediocre manager, a mediocre advisor & a mediocre PC at @nyuniversity (@CILVRatNYU) & @genentech (@PrescientDesign).
Lenka Zdeborova @zdeborova
13K Followers 421 Following Professor at EPFL. Une mathémaphysinformaticienne. Passionate mushroom hunter. Tamer of two little dragons.
Yu-Xiang Wang @yuxiangw_cs
2K Followers 280 Following Faculty @ucsbcs, director of ML lab. Previously @ScSatCMU and @awscloud. Researcher in #machinelearning, #reinforcementlearning, #differentialprivacy
Yiping Lu @2prime_PKU
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Amin Karbasi @aminkarbasi
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Dan Roy @roydanroy
45K Followers 2K Following ML / AI researcher, emphasis on theory. Research Director and Canada CIFAR AI Chair, @VectorInst Professor, @UofT (Statistics/CS)
Sam Power @sp_monte_carlo
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Elad Hazan @HazanPrinceton
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Dimitris Papailiopoul.. @DimitrisPapail
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NeurIPS Conference @NeurIPSConf
112K Followers 35 Following New Orleans, Dec 10-16, 23. https://t.co/ga8aOw615g Tweets to this account are not monitored. Please send feedback to [email protected].
Thomas Steinke @shortstein
9K Followers 454 Following Computer scientist interested in (differential) privacy & related topics, e.g., generalization. @GoogleDeepMind Opinions are mine ©. 🇳🇿
Jingfeng Yang @JingfengY
2K Followers 623 Following Applied Scientist @AmazonScience #LLMs #NLProc Formerly @SALT_NLP @Georgia_Tech @PKU1898 @Google @MSFTResearch . Opinions are my own.
Marc Lelarge 🌻 @marc_lelarge
5K Followers 595 Following Researcher in mathematics and machine learning @Inria and @ENS_ULM. Tweeting about maths and AI.
Ying Shan @yshan2u
1K Followers 576 Following Distinguished Scientist @TencentGlobal, Founder of PCG ARC Lab, Director of AI Lab Visual Computing. Formerly @Microsoft, @MSFTResearch. Views are my own.
ViktorM🇺🇦 @viktor_m81
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4K Followers 991 Following Senior Researcher @MSFTResearch. PhD from @Berkeley_EECS. #artificialintelligence #LLM #multimodal
@[email protected] @fperez_org
25K Followers 1K Following Physicist, data scientist, @IPythonDev creator (evolved to @ProjectJupyter). Assoc. Prof. UC Berkeley Stats, @BerkeleyLab scientist, @2i2c_org co-founder.
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3K Followers 319 Following Professor @UCSanDiego Dy. Director+AD for Research NSF AI Inst https://t.co/wblPm6DhUX, UCSD Site Lead @encoreinstitut Information Theory, Coding Th., Machine Learning
Yu Huang @yuhuang42
362 Followers 503 Following PhD student @Wharton Statistics｜CS MSc, Math Undergrad, @Tsinghua_Uni
Kaixuan Ji @Kaixuan_Ji_19
443 Followers 881 Following Ph.D. student in CS UCLA, B.E. from Tsinghua Uiversity. Interested in machine learning, especially RL Theory and LLM.
Praneeth Vepakomma @proneat
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Chara Podimata @charapod
754 Followers 368 Following Assistant Professor of OR/Stat at MIT. Past: postdoc UC Berkley, PhD Harvard. Interested in incentive-aware ML, bandits, mechanism design & public policy. 🏃♀️
Irene Chen @irenetrampoline
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335 Followers 130 Following
Steven Feng @stevenyfeng
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Christina Baek @_christinabaek
782 Followers 230 Following PhD student @mldcmu | Past: intern @GoogleAI
HaoyueBai @haoyue_bai
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Caltrain Alerts @CaltrainAlerts
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Jeff Dean (@🏡) @JeffDean
296K Followers 6K Following Chief Scientist, Google DeepMind and Google Research. Co-designer/implementor of things like @TensorFlow, MapReduce, Bigtable, Spanner, Gemini .. (he/him)
John Preskill @preskill
142K Followers 1K Following Theoretical physicist @Caltech, Director of @IQIM_Caltech, Amazon Scholar
Simons Institute for .. @SimonsInstitute
6K Followers 217 Following The world's leading venue for collaborative research in theoretical computer science. Follow us at https://t.co/KvcuGI7WM0.
American Mathematical.. @amermathsoc
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BIRS @BIRS_Math
5K Followers 245 Following The Banff International Research Station for Mathematical Innovation and Discovery, in the heart of the Canadian Rocky Mountains.
Lexing Ying @lexing_ying
5 Followers 54 Following
Marietje Schaake @MarietjeSchaake
70K Followers 25K Following [email protected] 📩 @stanfordcyber 👾 @StanfordHAI 💻 Columnist @FT 🇪🇺 MEP 2009-2019 📕Author of The Tech Coup 🌎 UN AI Advisory Body
Shane Gu @shaneguML
28K Followers 1K Following Research Scientist & Manager @GoogleDeepMind Tokyo/MTV. ex: @GoogleAI Brain, @OpenAI. (JP: @shanegJP)
Sophie Yu @SophieYu1014
377 Followers 323 Following Postdoc at @Stanford MS&E || Incoming Assistant Prof at @Wharton @Penn || Previously @DukeFuqua || Have a cat named Socky
Yonathan Efroni @EfroniYonathan
471 Followers 384 Following RL | ML | Music | etc Research scientist @Meta
Judea Pearl @yudapearl
76K Followers 188 Following Student of causal inference, human reasoning, and history of ideas, all viewed through the sharp lens of artificial intelligence.
Jennifer Chayes @jenniferchayes
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James Whittington @jcrwhittington
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Alexander Huth @alex_ander
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Kaiyu Yang @KaiyuYang4
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Hao Su @haosu_twitr
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Max Tegmark @tegmark
145K Followers 29 Following Known as Mad Max for my unorthodox ideas and passion for adventure, my scientific interests range from artificial intelligence to the ultimate nature of reality
CRISPR-GPT: An LLM Agent for Automated Design of Gene-Editing Experiments abs: arxiv.org/abs/2404.18021 Introduces CRISPR-GPT, a tailor-made LLM agent for automated designing of gene-editing experiments. Focuses on breaking experiment design down to a variety of substeps that…
The latest chapter in the saga of using stochastic localization/denoising diffusions to sample from highly multi-modal Gibbs measures. With the amazing Brice Huang and Huy Tuan Pham. (1/4) arxiv.org/abs/2404.15651
Just gave a guest lecture on Bayesian Causal Inference at Williams College, with slides and R code at doi.org/10.7910/DVN/JO… which is an introduction to our review paper royalsocietypublishing.org/doi/10.1098/rs… @fabri_mealli @FanLiDuke (I never taught any Bayesian Statistics at Berkeley.)
Associate Teaching Professor Andrew Bray won an Instructional Technology and Innovation Micro Grant via the Office of Vice Provost for Undergrad Education for the project “Gradebook: A tool for easy, flexible, and accurate course grades.” #BerkeleyStats statistics.berkeley.edu/about/news/bra…
Now that it is official, my amazing student Chris Harshaw is joining the statistics department @Columbia as an Assistant Professor. Super proud of him. chrisharshaw.com
I’m excited to announce that in July 2025 I will be joining @UWaterloo as an Assistant Professor in the Department of Statistics and Actuarial Science! Until then, I will continue at Princeton as a DataX Postdoc Fellow, working with Boris Hanin. I have many exciting projects…
Delighted to be launching a Open Source Program Office (OSPO) at @BerkeleyDataSci , housed under @UCBIDS and led by Jarrod Millman, long-time scientific python developer and leader. Huge thanks to @SloanFoundation @epistemographer for their ongoing support for Scientific OSS!
Lead by @UCBIDS and Faculty Director @fperez_org, UC Berkeley is joining an ambitious effort to advance open source research, education and public service across the UC system! cdss.berkeley.edu/news/uc-berkel…
Treat dataset need to forget as negative data in preference data. Smart application of DPO
LLM unlearning was mostly based on variants of gradient ascent (GA), susceptible to catastrophic forgetting. We propose Negative Preference Optimization (NPO), demonstrating efficient unlearning on TOFU benchmark. w/ @RuiqiZhang0614 @ Licong Lin, @yubai01. arxiv.org/abs/2404.05868
An Overview of Diffusion Models: Applications, Guided Generation, Statistical Rates and Optimization ift.tt/FJiwevm
Earlier this month, current M.A. students and alums gathered at Cal Academy in San Francisco for food, fellowship, and networking. "I loved the event; the venue and dinner were of high quality: it made me feel appreciated as a grad student." #BerkeleyStats
The folks at @OpenAI and @ericschmidt were kind enough to give @AdtRaghunathan and me a generous gift to better understand supervision with weak models. We are honored to be awarded, and are looking forward to the exciting work that will come out of this !
Who said math department always has the most ugly building and worst offices? This, despite of being just a visitor office, gives a counter example!
Our new youTube channel: youtube.com/playlist?list=… Comments welcome!
@Song__Mei @RuiqiZhang0614 @yubai01 This is really cool work! We looked at Gradient Ascent based methods only as a baseline in our 2019 work (arxiv.org/abs/1911.04933). Its nice to see that direction being extended to LLMs!
Check out the ICML workshop on Theoretical Foundations of Foundation Models!
We are happy to announce that the Workshop on Theoretical Foundations of Foundation Models will take place @icmlconf in Vienna! For details: sites.google.com/view/tf2m Organizers: @BerivanISIK, @SZiteng, @BanghuaZ, @eaboix, @nmervegurel, @uiuc_aisecure, @abeirami, @sanmikoyejo
I got ~75% on a subset of MATH so it's basically as good as me at math.
Our new GPT-4 Turbo is now available to paid ChatGPT users. We’ve improved capabilities in writing, math, logical reasoning, and coding. Source: github.com/openai/simple-…
Just updated our codebase for white-box transformer CRATE: github.com/Ma-Lab-Berkele… noticed that it has reached about 1K stars since its release a few month ago. Not so bad for a theoretical framework. With a working theoretical framework, we anticipate things now will progress…
Traveling to Seoul tomorrow for our tutorial about white-box deep networks on Sunday. Hope to see you there! cmsworkshops.com/ICASSP2024/tut…
Very cool result. Somewhat surprising how much one can achieve with the additional 1 in the log loss
LLM unlearning was mostly based on variants of gradient ascent (GA), susceptible to catastrophic forgetting. We propose Negative Preference Optimization (NPO), demonstrating efficient unlearning on TOFU benchmark. w/ @RuiqiZhang0614 @ Licong Lin, @yubai01. arxiv.org/abs/2404.05868
Exciting opportunity for working with Song on LLMs!
My group at Berkeley Stats and EECS has a postdoc opening in the theoretical (e.g., scaling laws, watermark) and empirical aspects (e.g., efficiency, safety, alignment) of LLMs or diffusion models. Send me an email with your CV if interested!
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