We build a Transformer-based molecule encoder and property predictor network with novel input featurization that performs significantly better than existing methods.
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.
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.
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.