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ORCIDTodd Hylton
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2020 – today
- 2022
[j4]Todd Hylton
:
Thermodynamic State Machine Network. Entropy 24(6): 744 (2022)- 2021
- [j3]Todd Hylton, Thomas M. Conte, Mark D. Hill:
A vision to compute like nature: thermodynamically. Commun. ACM 64(6): 35-38 (2021) - [e1]Thomas E. Potok, Melika Payvand, Catherine D. Schuman, Prasanna Date, Mutsumi Kimura, Cory E. Merkel, Brad Aimone, Sonia M. Buckley, Yiran Chen, Gregory Cohen, Todd Hylton, Robert M. Patton, Robinson E. Pino, Garrett S. Rose:
ICONS 2021: International Conference on Neuromorphic Systems 2021, Knoxville, TN, USA, July 27-29, 2021. ACM 2021, ISBN 978-1-4503-8691-3 [contents] - 2020
- [j2]Todd Hylton:
Thermodynamic Neural Network. Entropy 22(3): 256 (2020)
2010 – 2019
- 2019
- [j1]Jeffrey L. Krichmar, Tiffany Hwu, Xinyun Zou, Todd Hylton:
Advantage of prediction and mental imagery for goal-directed behaviour in agents and robots. Cogn. Comput. Syst. 1(1): 12-19 (2019) - [i5]Tom Conte, Erik DeBenedictis, Natesh Ganesh, Todd Hylton, John Paul Strachan, R. Stanley Williams, Alexander A. Alemi, Lee Altenberg, Gavin E. Crooks, James P. Crutchfield, Lídia del Rio, Josh Deutsch, Michael Robert DeWeese, Khari Douglas, Massimiliano Esposito, Michael P. Frank, Robert Fry, Peter Harsha, Mark D. Hill, Christopher T. Kello, Jeff Krichmar, Suhas Kumar, Shih-Chii Liu, Seth Lloyd, Matteo Marsili, Ilya Nemenman, Alex Nugent, Norman H. Packard, Dana Randall, Peter Sadowski, Narayana Santhanam, Robert Shaw, Adam Z. Stieg, Elan Stopnitzky, Christof Teuscher, Chris Watkins, David H. Wolpert, J. Joshua Yang, Yan Yufik:
Thermodynamic Computing. CoRR abs/1911.01968 (2019) - [i4]Michael Hazoglou, Todd Hylton:
Integrating Motion into Vision Models for Better Visual Prediction. CoRR abs/1912.01661 (2019) - 2018
- [i3]Michael Hazoglou, Todd Hylton:
Saccadic Predictive Vision Model with a Fovea. CoRR abs/1808.00597 (2018) - 2016
- [i2]Filip Piekniewski, Patryk A. Laurent, Csaba Petre, Micah Richert, Dimitry Fisher, Todd Hylton:
Unsupervised Learning from Continuous Video in a Scalable Predictive Recurrent Network. CoRR abs/1607.06854 (2016) - [i1]Micah Richert, Dimitry Fisher, Filip Piekniewski, Eugene M. Izhikevich, Todd Hylton:
Fundamental principles of cortical computation: unsupervised learning with prediction, compression and feedback. CoRR abs/1608.06277 (2016)
Coauthor Index
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