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ORCIDRaphael Norman-Tenazas
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2020 – today
- 2024
[c5]Raphael Norman-Tenazas
, Cameron Hickert, Tamim Sookoor, Aurora C. Schmidt, Edward Staley, Joseph Maurio, Jesse Silverberg, Paul Wood, Yair Amir:
Towards Trustworthy Distributed AI Demand Response. ICAA 2024: 106-109- [i2]Raphael Norman-Tenazas, David Kleinberg, Erik C. Johnson, Daniel P. Lathrop, Matthew J. Roos:
Using evolutionary computation to optimize task performance of unclocked, recurrent Boolean circuits in FPGAs. CoRR abs/2403.13105 (2024) - 2023
- [c4]Raphael Norman-Tenazas, David Kleinberg, Erik C. Johnson, Daniel P. Lathrop, Matthew J. Roos:
Using Evolutionary Computation to Optimize Task Performance of Unclocked, Recurrent Boolean Circuits in FPGAs. ACSSC 2023: 1564-1568 - [c3]Raphael Norman-Tenazas, Isaac Western, Gautam K. Vallabha, Matthew J. Roos, Erik C. Johnson, Brian S. Robinson:
Enabling local learning for generative-replay-based continual learning with a recurrent model of the insect memory center. ICONS 2023: 25:1-25:7 - [i1]Erik C. Johnson, Brian S. Robinson, Gautam K. Vallabha, Justin Joyce, Jordan K. Matelsky, Raphael Norman-Tenazas, Isaac Western, Marisel Villafañe-Delgado, Martha Cervantes, Michael S. Robinette, Arun V. Reddy, Lindsey Kitchell, Patricia K. Rivlin, Elizabeth Perez Reilly, Nathan Drenkow, Matthew J. Roos, I-Jeng Wang, Brock A. Wester, William R. Gray Roncal, Joan A. Hoffmann:
Exploiting Large Neuroimaging Datasets to Create Connectome-Constrained Approaches for more Robust, Efficient, and Adaptable Artificial Intelligence. CoRR abs/2305.17300 (2023) - 2022
- [c2]Raphael Norman-Tenazas, Brian S. Robinson, Justin Joyce, Isaac Western, Erik C. Johnson, William R. Gray Roncal, Joan A. Hoffmann:
Continuous State Estimation With Synapse-constrained Connectivity. IJCNN 2022: 1-9
2010 – 2019
- 2019
- [c1]Erik C. Johnson, Luis M. Rodriguez, Raphael Norman-Tenazas, Daniel Xenes, William R. Gray Roncal:
Transfer Learning Analysis of Image Processing Workflows for Electron Microscopy Datasets. ACSSC 2019: 1197-1201
Coauthor Index
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