Todd Hylton

According to our database, Todd Hylton authored at least 9 papers between 2016 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2022

Thermodynamic State Machine Network.

Todd Hylton

Entropy, 2022

2021

A vision to compute like nature: thermodynamically.

Todd Hylton, Thomas M. Conte, Mark D. Hill

Commun. ACM, 2021

2020

Thermodynamic Neural Network.

Todd Hylton

Entropy, 2020

2019

Integrating Motion into Vision Models for Better Visual Prediction.

Michael Hazoglou, Todd Hylton

CoRR, 2019

Thermodynamic Computing.

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

CoRR, 2019

Advantage of prediction and mental imagery for goal-directed behaviour in agents and robots.

Jeffrey L. Krichmar, Tiffany Hwu, Xinyun Zou, Todd Hylton

Cogn. Comput. Syst., 2019

2018

Saccadic Predictive Vision Model with a Fovea.

Michael Hazoglou, Todd Hylton

CoRR, 2018

2016

Fundamental principles of cortical computation: unsupervised learning with prediction, compression and feedback.

Micah Richert, Dimitry Fisher, Filip Piekniewski, Eugene M. Izhikevich, Todd Hylton

CoRR, 2016

Unsupervised Learning from Continuous Video in a Scalable Predictive Recurrent Network.

Filip Piekniewski, Patryk A. Laurent, Csaba Petre, Micah Richert, Dimitry Fisher, Todd Hylton

CoRR, 2016