2 code implementations • 21 Sep 2021 • Soukayna Mouatadid, Paulo Orenstein, Genevieve Flaspohler, Miruna Oprescu, Judah Cohen, Franklyn Wang, Sean Knight, Maria Geogdzhayeva, Sam Levang, Ernest Fraenkel, Lester Mackey
We develop a subseasonal forecasting toolkit of simple learned benchmark models that outperform both operational practice and state-of-the-art machine learning and deep learning methods.
no code implementations • 15 Apr 2021 • Michael Neumann, Oliver Roesler, Jackson Liscombe, Hardik Kothare, David Suendermann-Oeft, David Pautler, Indu Navar, Aria Anvar, Jochen Kumm, Raquel Norel, Ernest Fraenkel, Alexander V. Sherman, James D. Berry, Gary L. Pattee, Jun Wang, Jordan R. Green, Vikram Ramanarayanan
Our results provide encouraging evidence of the utility of automatically extracted audiovisual analytics for scalable remote patient assessment and monitoring in ALS.
We introduce Graph-Sparse Logistic Regression, a new algorithm for classification for the case in which the support should be sparse but connected on a graph.
We use a latent tree graphical model to analyze gene expression without relying on transcription factor expression as a proxy for regulator activity.
Single-cell RNA sequencing can now be used to measure the gene expression profiles of individual neurons and to categorize neurons based on their gene expression profiles.