SegICP-DSR: Dense Semantic Scene Reconstruction and Registration. - Jay Ming Wong; Syler Wagner; Richard Connor Lawson; Vincent Kee; Mitchell Hebert; Justin Rooney; Gian Luca Mariottini; Rebecca L. Russell; Abraham Schneider; Rahul Chipalkatty; David M. S. Johnson (CoRR, 2017)

Automated Vulnerability Detection in Source Code Using Deep Representation Learning. - Rebecca L. Russell; Louis Y. Kim; Lei H. Hamilton; Tomo Lazovich; Jacob Harer; Onur Ozdemir; Paul M. Ellingwood; Marc W. McConley (ICMLA, 2018)

Real-Time Object Pose Estimation with Pose Interpreter Networks. - Jimmy Wu; Bolei Zhou; Rebecca L. Russell; Vincent Kee; Syler Wagner; Mitchell Hebert; Antonio Torralba 001; David M. S. Johnson (IROS, 2018)

Learning to Repair Software Vulnerabilities with Generative Adversarial Networks. - Jacob Harer; Onur Ozdemir; Tomo Lazovich; Christopher P. Reale; Rebecca L. Russell; Louis Y. Kim; Peter Chin 001 (NeurIPS, 2018)

Automated software vulnerability detection with machine learning. - Jacob A. Harer; Louis Y. Kim; Rebecca L. Russell; Onur Ozdemir; Leonard R. Kosta; Akshay Rangamani; Lei H. Hamilton; Gabriel I. Centeno; Jonathan R. Key; Paul M. Ellingwood; Marc W. McConley; Jeffrey M. Opper; et al. (CoRR, 2018)

Explaining Conditions for Reinforcement Learning Behaviors from Real and Imagined Data. - Aastha Acharya; Rebecca L. Russell; Nisar R. Ahmed (CoRR, 2020)

A 3D Probabilistic Deep Learning System for Detection and Diagnosis of Lung Cancer Using Low-Dose CT Scans. - Onur Ozdemir; Rebecca L. Russell; Andrew A. Berlin (IEEE Trans. Medical Imaging, 2020)

Competency Assessment for Autonomous Agents using Deep Generative Models. - Aastha Acharya; Rebecca L. Russell; Nisar R. Ahmed (IROS, 2022)

Uncertainty Quantification for Competency Assessment of Autonomous Agents. - Aastha Acharya; Rebecca L. Russell; Nisar R. Ahmed (CoRR, 2022)

Learning and Understanding a Disentangled Feature Representation for Hidden Parameters in Reinforcement Learning. - Christopher P. Reale; Rebecca L. Russell (CoRR, 2022)

Symmetry Detection in Trajectory Data for More Meaningful Reinforcement Learning Representations. - Marissa D'Alonzo; Rebecca L. Russell (CoRR, 2022)

Multivariate Uncertainty in Deep Learning. - Rebecca L. Russell; Christopher P. Reale (IEEE Trans. Neural Networks Learn. Syst., 2022)

Learning to Forecast Aleatoric and Epistemic Uncertainties over Long Horizon Trajectories. - Aastha Acharya; Rebecca L. Russell; Nisar R. Ahmed (ICRA, 2023)

Wide-Area Geolocalization with a Limited Field of View Camera. - Lena M. Downes; Ted J. Steiner; Rebecca L. Russell; Jonathan P. How (ICRA, 2023)

Surrogate Neural Networks for Efficient Simulation-based Trajectory Planning Optimization. - Evelyn Ruff; Rebecca L. Russell; Matthew Stoeckle; Piero Miotto; Jonathan P. How (CoRR, 2023)

Wide-Area Geolocalization with a Limited Field of View Camera in Challenging Urban Environments. - Lena M. Downes; Ted J. Steiner; Rebecca L. Russell; Jonathan P. How (CoRR, 2023)

Wide-Area Geolocalization with a Limited Field of View Camera in Challenging Urban Environments Dataset. - Lena M. Downes; Ted J. Steiner; Rebecca L. Russell; Jonathan P. How (Zenodo, 2023)

Deep Modeling of Non-Gaussian Aleatoric Uncertainty. - Aastha Acharya; Caleb Lee; Marissa D'Alonzo; Jared Shamwell; Nisar R. Ahmed; Rebecca L. Russell (IEEE Robotics Autom. Lett., 2025)