Publications

Nicole Mitchell, Johannes Ballé, Zachary Charles, Jakub Konečný (2022). Optimizing the Communication-Accuracy Trade-off in Federated Learning with Rate-Distortion Theory. CoRR.

Nicole Elyse Mitchell (2020). Machine Learning-Based Prediction of Sites of Metabolism in Drugs: Exploring Feature Extraction Methods on Molecular Graphs. Master’s Thesis, Rice University.

Eleni Litsa, Nicole Mitchell, Lydia E Kavraki (2019). Applying Graph Convolutional Neural Networks for Drug Metabolism Prediction. 29th Annual Keck Research Conference, Rice Data Science Conference.

Didier Devaurs, Dinler A Antunes, Sarah Hall-Swan, Nicole Mitchell, Mark Moll, Gregory Lizée, Lydia E Kavraki (2019). Using parallelized incremental meta-docking can solve the conformational sampling issue when docking large ligands to proteins. BMC Molecular and Cell Biology.

Nicole Mitchell, Lucy Fox (2019). Road Identification in Satellite Images Using Image Segmentation Approaches. Rice University Statistical Machine Learning Poster Session.

Nicole Mitchell, Didier Devaurs, Lydia E Kavraki (2018). Evaluating DINC 2.0: An Improved Version of an Incremental Docking Protocol for Large Ligands. Rice Undergraduate Research Symposium.