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Eric Mitchell
Researcher at Samsung
Publications - 43
Citations - 595
Eric Mitchell is an academic researcher from Samsung. The author has contributed to research in topics: Computer science & Biology. The author has an hindex of 6, co-authored 22 publications receiving 153 citations. Previous affiliations of Eric Mitchell include Stanford University & Princeton University.
Papers
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Posted ContentDOI
FlyWire: Online community for whole-brain connectomics
Sven Dorkenwald,Claire E McKellar,Thomas Macrina,Nico Kemnitz,Kisuk Lee,Kisuk Lee,Ran Lu,Jingpeng Wu,Sergiy Popovych,Eric Mitchell,Barak Nehoran,Zhen Jia,J. Alexander Bae,Shang Mu,Dodam Ih,Manuel Castro,Oluwaseun Ogedengbe,Akhilesh Halageri,Zoe C. Ashwood,Jonathan Zung,Derrick Brittain,Forrest Collman,Casey M Schneider-Mizell,Chris S. Jordan,William Silversmith,Christa A. Baker,David Deutsch,Lucas Encarnacion-Rivera,Sandeep Kumar,Austin Burke,Jay Gager,James Hebditch,Selden Koolman,Merlin Moore,Sarah Morejohn,Ben Silverman,Kyle Willie,Ryan Willie,Szi-chieh Yu,Mala Murthy,H. Sebastian Seung +40 more
TL;DR: FlyWire, an online community for proofreading neural circuits in a fly brain, is presented and it is demonstrated how FlyWire enables circuit analysis by reconstructing and analysing the connectome of mechanosensory neurons.
Posted ContentDOI
Functional connectomics spanning multiple areas of mouse visual cortex
J. Alexander Bae,Mahaly Baptiste,Agnes L. Bodor,Derrick Brittain,JoAnn Buchanan,Daniel J. Bumbarger,Manuel Castro,Brendan Celii,Brendan Celii,Erick Cobos,Forrest Collman,Nuno Maçarico da Costa,Sven Dorkenwald,Leila Elabbady,Paul G. Fahey,Tim P. Fliss,Emmanouil Froudarakis,Emmanouil Froudarakis,Jay Gager,Clare Gamlin,Akhilesh Halageri,James Hebditch,Zhen Jia,Chris S. Jordan,Daniel Kapner,Nico Kemnitz,Sam Kinn,Selden Koolman,Kai Kuehner,Kisuk Lee,Kisuk Lee,Kai Li,Ran Lu,Thomas Macrina,Gayathri Mahalingam,Sarah McReynolds,Elanine Miranda,Eric Mitchell,Shanka Subhra Mondal,Merlin Moore,Shang Mu,Taliah Muhammad,Barak Nehoran,Oluwaseun Ogedengbe,Christos Papadopoulos,Stelios Papadopoulos,Saumil S. Patel,Xaq Pitkow,Xaq Pitkow,Sergiy Popovych,Anthony Ramos,R. Clay Reid,Jacob Reimer,Casey M Schneider-Mizell,H. Sebastian Seung,Ben Silverman,William Silversmith,Amy L. R. Sterling,Fabian H. Sinz,Cameron Smith,Shelby Suckow,Marc Takeno,Zheng H Tan,Andreas S. Tolias,Andreas S. Tolias,Russel Torres,Nicholas L. Turner,Edgar Y. Walker,Tianyu Wang,Grace Williams,Sarah Williams,Kyle Willie,Ryan Willie,William Wong,Jingpeng Wu,Chris Xu,Runzhe Yang,Dimitri Yatsenko,Fei Ye,Wenjing Yin,Szi-chieh Yu +80 more
TL;DR: In this paper, the authors present a unique functional connectomics dataset that contains calcium imaging of an estimated 75,000 neurons from primary visual cortex (VISp) and three higher visual areas (VISrl, VISal and VISlm), that were recorded while a mouse viewed natural movies and parametric stimuli.
Posted Content
On the Opportunities and Risks of Foundation Models.
Rishi Bommasani,Drew A. Hudson,Ehsan Adeli,Russ B. Altman,Simran Arora,Sydney von Arx,Michael S. Bernstein,Jeannette Bohg,Antoine Bosselut,Emma Brunskill,Erik Brynjolfsson,Shyamal Buch,Dallas Card,Rodrigo Castellon,Niladri S. Chatterji,Annie Chen,Kathleen Creel,Jared Davis,Dora Demszky,Chris Donahue,Moussa Doumbouya,Esin Durmus,Stefano Ermon,John Etchemendy,Kawin Ethayarajh,Li Fei-Fei,Chelsea Finn,Trevor Gale,Lauren Gillespie,Karan Goel,Noah D. Goodman,Shelby Grossman,Neel Guha,Tatsunori Hashimoto,Peter Henderson,John Hewitt,Daniel E. Ho,Jenny Hong,Kyle Hsu,Jing Huang,Thomas Icard,Saahil Jain,Dan Jurafsky,Pratyusha Kalluri,Siddharth Karamcheti,Geoff Keeling,Fereshte Khani,Omar Khattab,Pang Wei Koh,Mark Krass,Ranjay Krishna,Rohith Kuditipudi,Ananya Kumar,Faisal Ladhak,Mina Lee,Tony Lee,Jure Leskovec,Isabelle Levent,Xiang Lisa Li,Xuechen Li,Tengyu Ma,Ali Ahmad Malik,Christopher D. Manning,Suvir Mirchandani,Eric Mitchell,Zanele Munyikwa,Suraj Nair,Avanika Narayan,Deepak Narayanan,Ben Newman,Allen Nie,Juan Carlos Niebles,Hamed Nilforoshan,Julian Nyarko,Giray Ogut,Laurel Orr,Isabel Papadimitriou,Joon Sung Park,Chris Piech,Eva Portelance,Christopher Potts,Aditi Raghunathan,Rob Reich,Hongyu Ren,Frieda Rong,Yusuf H. Roohani,Camilo Ruiz,Jack Ryan,Christopher Ré,Dorsa Sadigh,Shiori Sagawa,Keshav Santhanam,Andy Shih,Krishnan Srinivasan,Alex Tamkin,Rohan Taori,Armin W. Thomas,Florian Tramèr,Rose E. Wang,William Yang Wang,Bohan Wu,Jiajun Wu,Yuhuai Wu,Sang Michael Xie,Michihiro Yasunaga,Jiaxuan You,Matei Zaharia,Michael Zhang,Tianyi Zhang,Xikun Zhang,Yuhui Zhang,Lucia Zheng,Kaitlyn Zhou,Percy Liang +113 more
TL;DR: The authors provides a thorough account of the opportunities and risks of foundation models, ranging from their capabilities (e.g., language, vision, robotics, reasoning, human interaction) and technical principles(e. g.g. model architectures, training procedures, data, systems, security, evaluation, theory) to their applications.
Journal ArticleDOI
DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature
TL;DR: In this article , Mitchell et al. demonstrate that text sampled from an LLM tends to occupy negative curvature regions of the model's log probability function and define a new curvature-based criterion for judging if a passage is generated from a given LLM.
Posted Content
Offline Meta-Reinforcement Learning with Advantage Weighting
TL;DR: This paper introduces the offline meta-reinforcement learning (offline meta-RL) problem setting and proposes an algorithm that performs well in this setting, and proposes MACAW, an optimization-based meta-learning algorithm that uses simple, supervised regression objectives for both the inner and outer loop of meta-training.