Epstein Secrets

ing. Neural Computing, 10:251-276, 1998. ANOO. Shun-ichi Amari and Hiroshi Nagaoka. Methods of information geometry. ANIS, 2000. ARC09a. I. Aral, D. Rose, and R. Coop. Destin: A scalable deep learning architecture with application to high-dimensional robust pattern recognition. Proc. AAA! Workshop on

ata describing something to a hypothesis that accounts for the data. Often in an OpenCog context, this refers to the PLN abduction rule, a specific First-Order PLN rule (If A implies C, and B implies C, then maybe A is B), which embodies a simple form of abductive inference. But OpenCog may also carry out abdu

Daniel J. Amit. Modeling brain function - the world of attractor neural networks. Cambridge University Press, New York, USA, 1989. ARC09. I. Arel, D. Rose, and R. Coop. Destin: A scalable deep learning architecture with application to high-dimensional robust pattern recognition. Proc. AAA! Workshop on

ata describing something to a hypothesis that accounts for the data. Often in an OpenCog context, this refers to the PLN abduction rule, a specific First-Order PLN rule (If A implies C, and B implies C, then maybe A is B), which embodies a simple form of abductive inference. But OpenCog may also carry out abdu

. Daniel J. Amit. Modeling brain function — the world of attractor neural networks. Cambridge University Press, New York, USA, 1989. ARCO9. I. Arel, D. Rose, and R. Coop. Destin: A scalable deep learning architecture with application to high-dimensional robust pattern recognition. Proc. AAAI Workshop on B

data describing something to a hypothesis that accounts for the data. Often in an OpenCog context, this refers to the PLN abduction rule, a specific First-Order PLN rule (If A implies C, and B implies C, then maybe A is B), which embodies a simple form of abductive inference. But OpenCog may also carry out abduct