Scalable and accurate deep learning for electronic health records. - Alvin Rajkomar; Eyal Oren; Kai Chen 010; Andrew M. Dai; Nissan Hajaj; Peter J. Liu; Xiaobing Liu; Mimi Sun; Patrik Sundberg; Hector Yee; Kun Zhang 043; Gavin E. Duggan; et al. (CoRR, 2018)

Scalable and accurate deep learning with electronic health records. - Alvin Rajkomar; Eyal Oren; Kai Chen 010; Andrew M. Dai; Nissan Hajaj; Michaela Hardt; Peter J. Liu; Xiaobing Liu; Jake Marcus; Mimi Sun; Patrik Sundberg; Hector Yee; et al. (npj Digit. Medicine, 2018)

Modelling EHR timeseries by restricting feature interaction. - Kun Zhang 043; Yuan Xue; Gerardo Flores; Alvin Rajkomar; Claire Cui; Andrew M. Dai (CoRR, 2019)

Deep Physiological State Space Model for Clinical Forecasting. - Yuan Xue; Denny Zhou; Nan Du 002; Andrew M. Dai; Zhen Xu 006; Kun Zhang 043; Claire Cui (CoRR, 2019)

Explaining an increase in predicted risk for clinical alerts. - Michaela Hardt; Alvin Rajkomar; Gerardo Flores; Andrew M. Dai; Michael D. Howell; Greg Corrado; Claire Cui; Moritz Hardt (CHIL, 2020)

Deep State-Space Generative Model For Correlated Time-to-Event Predictions. - Yuan Xue; Denny Zhou; Nan Du 002; Andrew M. Dai; Zhen Xu 006; Kun Zhang 043; Claire Cui (KDD, 2020)

Beyond Point Estimate: Inferring Ensemble Prediction Variation from Neuron Activation Strength in Recommender Systems. - Zhe Chen; Yuyan Wang; Dong Lin; Derek Zhiyuan Cheng; Lichan Hong; Ed H. Chi; Claire Cui (WSDM, 2021)

GLaM: Efficient Scaling of Language Models with Mixture-of-Experts. - Nan Du 002; Yanping Huang; Andrew M. Dai; Simon Tong; Dmitry Lepikhin; Yuanzhong Xu; Maxim Krikun; Yanqi Zhou; Adams Wei Yu; Orhan Firat; Barret Zoph; Liam Fedus; et al. (ICML, 2022)

LaMDA: Language Models for Dialog Applications. - Romal Thoppilan; Daniel De Freitas; Jamie Hall; Noam Shazeer; Apoorv Kulshreshtha; Heng-Tze Cheng; Alicia Jin; Taylor Bos; Leslie Baker; Yu Du; YaGuang Li; Hongrae Lee; et al. (CoRR, 2022)

Mind's Eye: Grounded Language Model Reasoning through Simulation. - Ruibo Liu; Jason Wei; Shixiang Shane Gu; Te-Yen Wu; Soroush Vosoughi; Claire Cui; Denny Zhou; Andrew M. Dai (ICLR, 2023)

Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. - Denny Zhou; Nathanael Schärli; Le Hou; Jason Wei; Nathan Scales; Xuezhi Wang 002; Dale Schuurmans; Claire Cui; Olivier Bousquet; Quoc V. Le; Ed H. Chi (ICLR, 2023)

Lifelong Language Pretraining with Distribution-Specialized Experts. - Wuyang Chen 001; Yanqi Zhou; Nan Du 002; Yanping Huang; James Laudon; Zhifeng Chen; Claire Cui (ICML, 2023)

Brainformers: Trading Simplicity for Efficiency. - Yanqi Zhou; Nan Du 002; Yanping Huang; Daiyi Peng; Chang Lan; Da Huang; Siamak Shakeri; David R. So; Andrew M. Dai; Yifeng Lu; Zhifeng Chen; Quoc V. Le; et al. (ICML, 2023)

Learning to Skip for Language Modeling. - Dewen Zeng; Nan Du 002; Tao Wang; Yuanzhong Xu; Tao Lei; Zhifeng Chen; Claire Cui (CoRR, 2023)

MaMMUT: A Simple Architecture for Joint Learning for MultiModal Tasks. - Weicheng Kuo; A. J. Piergiovanni; Dahun Kim; Xiyang Luo; Benjamin Caine; Wei Li 133; Abhijit S. Ogale; Luowei Zhou; Andrew M. Dai; Zhifeng Chen; Claire Cui; Anelia Angelova (Trans. Mach. Learn. Res., 2023)

Capabilities of Gemini Models in Medicine. - Khaled Saab 003; Tao Tu 001; Wei-Hung Weng; Ryutaro Tanno; David Stutz; Ellery Wulczyn; Fan Zhang; Tim Strother; Chunjong Park; Elahe Vedadi; Juanma Zambrano Chaves; Szu-Yeu Hu; et al. (CoRR, 2024)