Author: John Byrnes
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Transformer Based Molecule Encoding for Property Prediction
We build a Transformer-based molecule encoder and property predictor network with novel input featurization that performs significantly better than existing methods.
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Deep Adaptive Semantic Logic (DASL): Compiling Declarative Knowledge into Deep Neural Networks
We introduce Deep Adaptive Semantic Logic (DASL), a novel framework for automating the generation of deep neural networks that incorporates user-provided formal knowledge to improve learning from data.
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Application of Text Analytics to Extract and Analyze Material–Application Pairs from a Large Scientific Corpus
In this work, we have successfully extracted material–application pairs and ranked them on their importance. This method provides a novel way to map scientific advances in a particular material to the application for which it is used.
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Spatial and Temporal Patterns in Preterm Birth in the United States
In order to help generate new research hypotheses, this study explored spatial and temporal patterns of preterm birth in a large, total-population dataset.