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ORCIDCory Y. McLean
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Books and Theses
- 2011
[b1]Cory Y. McLean:
Computational analysis of the mammalian cis-regulatory landscape. Stanford University, USA, 2011
Journal Articles
- 2022
- [j3]Alexander D'Amour, Katherine A. Heller, Dan Moldovan, Ben Adlam, Babak Alipanahi, Alex Beutel, Christina Chen, Jonathan Deaton, Jacob Eisenstein, Matthew D. Hoffman, Farhad Hormozdiari, Neil Houlsby, Shaobo Hou, Ghassen Jerfel, Alan Karthikesalingam, Mario Lucic, Yi-An Ma, Cory Y. McLean, Diana Mincu, Akinori Mitani, Andrea Montanari, Zachary Nado, Vivek Natarajan, Christopher Nielson, Thomas F. Osborne, Rajiv Raman, Kim Ramasamy, Rory Sayres, Jessica Schrouff, Martin Seneviratne, Shannon Sequeira, Harini Suresh, Victor Veitch, Max Vladymyrov, Xuezhi Wang, Kellie Webster, Steve Yadlowsky, Taedong Yun, Xiaohua Zhai, D. Sculley:
Underspecification Presents Challenges for Credibility in Modern Machine Learning. J. Mach. Learn. Res. 23: 226:1-226:61 (2022) - 2021
- [j2]Taedong Yun
, Helen Li, Pi-Chuan Chang, Michael F. Lin, Andrew Carroll, Cory Y. McLean:
Accurate, scalable cohort variant calls using DeepVariant and GLnexus. Bioinform. 36(24): 5582-5589 (2021) - 2019
- [j1]Cory Y. McLean, Yeongwoo Hwang, Ryan Poplin, Mark A. DePristo:
GenomeWarp: an alignment-based variant coordinate transformation. Bioinform. 35(21): 4389-4391 (2019)
Conference and Workshop Papers
- 2023
- [c2]Anastasiya Belyaeva, Justin Cosentino, Farhad Hormozdiari, Krish Eswaran, Shravya Shetty, Greg Corrado, Andrew Carroll, Cory Y. McLean, Nicholas A. Furlotte:
Multimodal LLMs for Health Grounded in Individual-Specific Data. ML4MHD 2023: 86-102 - 2021
- [c1]Steve Yadlowsky, Taedong Yun, Cory Y. McLean, Alexander D'Amour:
SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression. NeurIPS 2021: 29517-29528
Informal and Other Publications
- 2024
- [i8]Lin Yang, Shawn Xu, Andrew Sellergren, Timo Kohlberger, Yuchen Zhou, Ira Ktena, Atilla P. Kiraly, Faruk Ahmed, Farhad Hormozdiari, Tiam Jaroensri, Eric Wang, Ellery Wulczyn, Fayaz Jamil, Theo Guidroz, Chuck Lau, Siyuan Qiao, Yun Liu, Akshay Goel, Kendall Park, Arnav Agharwal, Nick George, Yang Wang, Ryutaro Tanno, David G. T. Barrett, Wei-Hung Weng, S. Sara Mahdavi, Khaled Saab, Tao Tu, Sreenivasa Raju Kalidindi, Mozziyar Etemadi, Jorge Cuadros, Gregory Sorensen, Yossi Matias, Katherine Chou, Greg Corrado, Joelle K. Barral, Shravya Shetty, David J. Fleet, S. M. Ali Eslami, Daniel Tse, Shruthi Prabhakara, Cory Y. McLean, Dave Steiner, Rory Pilgrim, Christopher Kelly, Shekoofeh Azizi, Daniel Golden:
Advancing Multimodal Medical Capabilities of Gemini. CoRR abs/2405.03162 (2024) - [i7]Mike A. Merrill, Akshay Paruchuri, Naghmeh Rezaei, Geza Kovacs, Javier Perez Matos, Yun Liu, Erik Schenck, Nova Hammerquist, Jake Sunshine, Shyam Tailor, Kumar Ayush, Hao-Wei Su, Qian He, Cory Y. McLean, Mark Malhotra, Shwetak N. Patel, Jiening Zhan, Tim Althoff, Daniel McDuff, Xin Liu:
Transforming Wearable Data into Health Insights using Large Language Model Agents. CoRR abs/2406.06464 (2024) - [i6]Justin Cosentino, Anastasiya Belyaeva, Xin Liu, Nicholas A. Furlotte, Zhun Yang, Chace Lee, Erik Schenck, Yojan Patel, Jian Cui, Logan Douglas Schneider, Robby Bryant, Ryan G. Gomes, Allen Jiang, Roy Lee, Yun Liu, Javier Perez Matos, Jameson K. Rogers, Cathy Speed, Shyam Tailor, Megan Walker, Jeffrey Yu, Tim Althoff, Conor Heneghan, John Hernandez, Mark Malhotra, Leor Stern, Yossi Matias, Gregory S. Corrado, Shwetak N. Patel, Shravya Shetty, Jiening Zhan, Shruthi Prabhakara, Daniel McDuff, Cory Y. McLean:
Towards a Personal Health Large Language Model. CoRR abs/2406.06474 (2024) - 2023
- [i5]Wei-Hung Weng, Sebastien Baur, Mayank Daswani, Christina Chen, Lauren Harrell, Sujay Kakarmath, Mariam Jabara, Babak Behsaz, Cory Y. McLean, Yossi Matias, Gregory S. Corrado, Shravya Shetty, Shruthi Prabhakara, Yun Liu, Goodarz Danaei, Diego Ardila:
Predicting Cardiovascular Disease Risk using Photoplethysmography and Deep Learning. CoRR abs/2305.05648 (2023) - [i4]Anastasiya Belyaeva, Justin Cosentino, Farhad Hormozdiari, Krish Eswaran, Shravya Shetty, Greg Corrado, Andrew Carroll, Cory Y. McLean, Nicholas A. Furlotte:
Multimodal LLMs for health grounded in individual-specific data. CoRR abs/2307.09018 (2023) - 2022
- [i3]Anastasiya Belyaeva, Joel Shor, Daniel E. Cook, Kishwar Shafin, Daniel Liu, Armin Töpfer, Aaron M. Wenger, William J. Rowell, Howard Yang, Alexey Kolesnikov, Cory Y. McLean, Maria Nattestad, Andrew Carroll, Pi-Chuan Chang:
Knowledge distillation for fast and accurate DNA sequence correction. CoRR abs/2211.09862 (2022) - 2021
- [i2]Steve Yadlowsky, Taedong Yun, Cory Y. McLean, Alexander D'Amour:
SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression. CoRR abs/2103.12725 (2021) - 2020
- [i1]Alexander D'Amour, Katherine A. Heller, Dan Moldovan, Ben Adlam, Babak Alipanahi, Alex Beutel, Christina Chen, Jonathan Deaton, Jacob Eisenstein, Matthew D. Hoffman, Farhad Hormozdiari, Neil Houlsby, Shaobo Hou, Ghassen Jerfel, Alan Karthikesalingam, Mario Lucic, Yi-An Ma, Cory Y. McLean, Diana Mincu, Akinori Mitani, Andrea Montanari, Zachary Nado, Vivek Natarajan, Christopher Nielson, Thomas F. Osborne, Rajiv Raman, Kim Ramasamy, Rory Sayres, Jessica Schrouff, Martin Seneviratne, Shannon Sequeira, Harini Suresh, Victor Veitch, Max Vladymyrov, Xuezhi Wang, Kellie Webster, Steve Yadlowsky, Taedong Yun, Xiaohua Zhai, D. Sculley:
Underspecification Presents Challenges for Credibility in Modern Machine Learning. CoRR abs/2011.03395 (2020)
Coauthor Index
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