25 citations · 64 across the 6 of their papers we have counts for
6 papers
Integrating Motion into Vision Models for Better Visual Prediction
Michael Hazoglou, Todd Hylton
We demonstrate an improved vision system that learns a model of its environment using a self-supervised, predictive learning method. The system includes a pan-tilt camera, a foveat…
Thermodynamic Computing
Tom Conte, Erik DeBenedictis, Natesh Ganesh +36
The hardware and software foundations laid in the first half of the 20th Century enabled the computing technologies that have transformed the world, but these foundations are now u…
Thermodynamic Neural Network
Todd Hylton
A thermodynamically motivated neural network model is described that self-organizes to transport charge associated with internal and external potentials while in contact with a the…
Saccadic Predictive Vision Model with a Fovea
Michael Hazoglou, Todd Hylton
We propose a model that emulates saccades, the rapid movements of the eye, called the Error Saccade Model, based on the prediction error of the Predictive Vision Model (PVM). The E…
Fundamental principles of cortical computation: unsupervised learning with prediction, compression and feedback
Micah Richert, Dimitry Fisher, Filip Piekniewski +2
There has been great progress in understanding of anatomical and functional microcircuitry of the primate cortex. However, the fundamental principles of cortical computation - the…
Unsupervised Learning from Continuous Video in a Scalable Predictive Recurrent Network
Filip Piekniewski, Patryk Laurent, Csaba Petre +3
Understanding visual reality involves acquiring common-sense knowledge about countless regularities in the visual world, e.g., how illumination alters the appearance of objects in…