Browsing by Author "Gehrmann, Sebastian"

Now showing items 1-4 of 4

    • Accelerating Antimicrobial Discovery With Controllable Deep Generative Models and Molecular Dynamics 

      Das, Payel; Sercu, Tom; Wadhawan, Kahini; Padhi, Inkit; Gehrmann, Sebastian; Cipcigan, Flaviu; Chenthamarakshan, Vijil; Strobelt, Hendrik; dos Santos, Cicero; Chen, Pin-Yu; Yang, Yi Yan; Tan, Jeremy P.K.; Hedrick, James; Crain, Jason; Mojsilovic, Aleksandra; Mojsilovic (2021-03-11)
      De novo therapeutic design is challenged by a vast chemical repertoire and multiple constraints such as high broad-spectrum potency and low toxicity. We propose CLaSS (Controlled Latent attribute Space Sampling) — an ...

    • Comparing deep learning and concept extraction based methods for patient phenotyping from clinical narratives 

      Gehrmann, Sebastian; Dernoncourt, Franck; Li, Yeran; Carlson, Eric T.; Wu, Joy T.; Welt, Jonathan; Foote, John; Moseley, Edward T.; Grant, David W.; Tyler, Patrick D.; Celi, Leo A. (Public Library of Science (PLoS), 2018)
      In secondary analysis of electronic health records, a crucial task consists in correctly identifying the patient cohort under investigation. In many cases, the most valuable and relevant information for an accurate ...

    • Deploying AI Methods to Support Collaborative Writing: A Preliminary Investigation 

      Gehrmann, Sebastian; Urke, Lauren; Amir, Ofra; Grosz, Barbara J. (2015)
      Many documents (e.g., academic papers, government reports) are typically written by multiple authors. While existing tools facilitate and support such collaborative efforts (e.g., Dropbox, Google Docs), these tools lack ...

    • LSTM Networks Can Perform Dynamic Counting 

      Suzgun, Mirac; Gehrmann, Sebastian; Belinkov, Yonatan; Shieber, Stuart (2019-06-09)
      In this paper, we systematically assess the ability of standard recurrent networks to perform dynamic counting and to encode hierarchical representations. All the neural models in our experiments are designed to be small-sized ...