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Journal Articles
- 2023
[j3]Megan M. Baker
, Alexander New, Mario Aguilar-Simon, Ziad Al-Halah, Sébastien M. R. Arnold, Eseoghene Ben-Iwhiwhu, Andrew P. Brna, Ethan Brooks, Ryan C. Brown, Zachary Daniels, Anurag Reddy Daram, Fabien Delattre, Ryan Dellana, Eric Eaton, Haotian Fu, Kristen Grauman, Jesse Hostetler, Shariq Iqbal, Cassandra Kent, Nicholas Ketz, Soheil Kolouri, George Konidaris, Dhireesha Kudithipudi, Erik G. Learned-Miller, Seungwon Lee, Michael Littman, Sandeep Madireddy, Jorge A. Mendez, Eric Q. Nguyen, Christine D. Piatko, Praveen K. Pilly, Aswin Raghavan, Abrar Rahman, Santhosh Kumar Ramakrishnan, Neale Ratzlaff, Andrea Soltoggio, Peter Stone, Indranil Sur, Zhipeng Tang, Saket Tiwari, Kyle Vedder, Felix Wang, Zifan Xu, Angel Yanguas-Gil, Harel Yedidsion, Shangqun Yu, Gautam K. Vallabha:
A domain-agnostic approach for characterization of lifelong learning systems. Neural Networks 160: 274-296 (2023)- 2019
- [j2]Andrew P. Brna, Ryan C. Brown, Patrick M. Connolly, Stephen B. Simons, Renee E. Shimizu, Mario Aguilar-Simon:
Uncertainty-based modulation for lifelong learning. Neural Networks 120: 129-142 (2019) - 2018
- [j1]Ryan C. Brown, Joshua Moser:
HSImage: A Python and C++ library to allow interaction with ENVI-BIL hyperspectral images. J. Open Source Softw. 3(25): 630 (2018)
Conference and Workshop Papers
- 2022
- [c2]Ryan C. Brown, Andrew P. Brna, Jared Cook, Samuel Park, Mario Aguilar-Simon:
Uncertainty-Driven Control for a Self-Supervised Lifelong Learning Drone. IGARSS 2022: 5053-5056 - 2016
- [c1]Craig S. Lent, Kenneth W. Henderson, S. Alex Kandel, Steven A. Corcelli, Gregory L. Snider, Alexei O. Orlov, Peter M. Kogge, Michael T. Niemier, Ryan C. Brown, John A. Christie, Natalie A. Wasio, Rebecca C. Quardokus, Ryan P. Forrest, Jacob P. Peterson, Angela Silski, David A. Turner, Enrique P. Blair, Yuhui Lu:
Molecular cellular networks: A non von Neumann architecture for molecular electronics. ICRC 2016: 1-7
Informal and Other Publications
- 2024
- [i3]David J. Schodt, Ryan C. Brown, Michael Merritt, Samuel Park, Delsin Menolascino, Mark A. Peot:
A Framework for Variational Inference of Lightweight Bayesian Neural Networks with Heteroscedastic Uncertainties. CoRR abs/2402.14532 (2024) - 2023
- [i2]Megan M. Baker, Alexander New, Mario Aguilar-Simon, Ziad Al-Halah, Sébastien M. R. Arnold, Eseoghene Ben-Iwhiwhu, Andrew P. Brna, Ethan Brooks, Ryan C. Brown, Zachary Daniels, Anurag Reddy Daram, Fabien Delattre, Ryan Dellana, Eric Eaton, Haotian Fu, Kristen Grauman, Jesse Hostetler, Shariq Iqbal, Cassandra Kent, Nicholas Ketz, Soheil Kolouri, George Dimitri Konidaris, Dhireesha Kudithipudi, Erik G. Learned-Miller, Seungwon Lee, Michael Littman, Sandeep Madireddy, Jorge A. Mendez, Eric Q. Nguyen, Christine D. Piatko, Praveen K. Pilly, Aswin Raghavan, Abrar Rahman, Santhosh Kumar Ramakrishnan, Neale Ratzlaff, Andrea Soltoggio, Peter Stone, Indranil Sur, Zhipeng Tang, Saket Tiwari, Kyle Vedder, Felix Wang, Zifan Xu, Angel Yanguas-Gil, Harel Yedidsion, Shangqun Yu, Gautam K. Vallabha:
A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems. CoRR abs/2301.07799 (2023) - 2020
- [i1]Andrew P. Brna, Ryan C. Brown, Patrick M. Connolly, Stephen B. Simons, Renee E. Shimizu, Mario Aguilar-Simon:
Uncertainty-based Modulation for Lifelong Learning. CoRR abs/2001.09822 (2020)
Coauthor Index
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