— Inspired by the universal laws governing different kinds of complex networks, we propose a scale-free highlyclustered echo state network (SHESN). Different from echo state netw...
The traditional paradigm for digital filter design is based on the concept of a linear difference equation with the output response being a weighted sum of signal samples with usua...
We propose a model of the hippocampus aimed at learning the timed association between subsequent sensory events. The properties of the neural network allow it to learn and predict ...
It is generally assumed in the traditional formulation of supervised learning that only the outputs data are uncertain. However, this assumption might be too strong for some learni...
Patrick Dallaire, Camille Besse, Brahim Chaib-draa
An important extension of satisfiability testing is model-counting, a task that corresponds to problems such as probabilistic reasoning and computing the permanent of a Boolean ma...