Rebecca L. Russell

According to our database, Rebecca L. Russell authored at least 18 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Deep Modeling of Non-Gaussian Aleatoric Uncertainty.

Aastha Acharya, Caleb Lee, Marissa D'Alonzo, Jared Shamwell, Nisar R. Ahmed, Rebecca L. Russell

CoRR, 2024

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

Dataset, April, 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

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.

Lena M. Downes, Ted J. Steiner, Rebecca L. Russell, Jonathan P. How

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Learning to Forecast Aleatoric and Epistemic Uncertainties over Long Horizon Trajectories.

Aastha Acharya, Rebecca L. Russell, Nisar R. Ahmed

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

2022

Multivariate Uncertainty in Deep Learning.

Rebecca L. Russell, Christopher P. Reale

IEEE Trans. Neural Networks Learn. Syst., 2022

Symmetry Detection in Trajectory Data for More Meaningful Reinforcement Learning Representations.

Marissa D'Alonzo, Rebecca L. Russell

CoRR, 2022

Learning and Understanding a Disentangled Feature Representation for Hidden Parameters in Reinforcement Learning.

Christopher P. Reale, Rebecca L. Russell

CoRR, 2022

Uncertainty Quantification for Competency Assessment of Autonomous Agents.

Aastha Acharya, Rebecca L. Russell, Nisar R. Ahmed

CoRR, 2022

Competency Assessment for Autonomous Agents using Deep Generative Models.

Aastha Acharya, Rebecca L. Russell, Nisar R. Ahmed

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

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

Explaining Conditions for Reinforcement Learning Behaviors from Real and Imagined Data.

Aastha Acharya, Rebecca L. Russell, Nisar R. Ahmed

CoRR, 2020

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, Peter Chin, Tomo Lazovich

CoRR, 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

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 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, David M. S. Johnson

Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018

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

Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018

2017

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