Although there are many neural network FPGA architectures, there is no framework for designing large, high-performance neural networks suitable for the real world. In this paper, ...
Embryological electronics or “Embryonics” is a new paradigm for developing digital systems of any complexity, endowed of universal computation, self-repair and self-reproducti...
Daniel Mange, Serge Durand, Eduardo Sanchez, Andr&...
Randomized neural networks are immortalized in this well-known AI Koan: In the days when Sussman was a novice, Minsky once came to him as he sat hacking at the PDP-6. "What a...
Learning data representations is a fundamental challenge in modeling neural processes and plays an important role in applications such as object recognition. In multi-stage Optima...
A fundamental problem in neural network research, as well as in many other disciplines, is finding a suitable representation of multivariate data, i.e. random vectors. For reasons...