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Challenges and Solutions with Alignment and Enrichment of Word Embedding Models

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  1. Article

    Open Access

    Machine learning optimization of candidate antibody yields highly diverse sub-nanomolar affinity antibody libraries

    Therapeutic antibodies are an important and rapidly growing drug modality. However, the design and discovery of early-stage antibody therapeutics remain a time and cost-intensive endeavor. Here we present an e...

    Lin Li, Esther Gupta, John Spaeth, Leslie Shing, Rafael Jaimes… in Nature Communications (2023)

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  2. Article

    Open Access

    Explaining COVID-19 outbreaks with reactive SEIRD models

    COVID-19 epidemics have varied dramatically in nature across the United States, where some counties have clear peaks in infections, and others have had a multitude of unpredictable and non-distinct peaks. Our ...

    Kunal Menda, Lucas Laird, Mykel J. Kochenderfer, Rajmonda S. Caceres in Scientific Reports (2021)

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  3. Chapter and Conference Paper

    Handling Oversampling in Dynamic Networks Using Link Prediction

    Oversampling is a common characteristic of data representing dynamic networks. It introduces noise into representations of dynamic networks, but there has been little work so far to compensate for it. Oversamp...

    Benjamin Fish, Rajmonda S. Caceres in Machine Learning and Knowledge Discovery in Databases (2015)

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