A framework for Similarity-Based Methods (SBMs) includes many neural network models as special cases. Multilayer Perceptrons (MLPs) use scalar products to compute weighted activation of neurons, combining soft hyperplanes to provide decision borders. Scalar product is replaced by a distance function between the inputs and the weights, offering a natural generalization of the standard MLP model ...

Does motivational interest increase gamma synchrony across neuronal networking to enable computation of related sensory inputs that might lead to greater social understanding in autism spectrum conditions (ASC)? Meaning, is it possible/likely that in autism because individuals process one aspect of sensory input at any one time (therefore missing the wider picture in general) when they are moti...

An Input/Output Automaton is an automaton with a finite number of state where each transition is associated with a single input or output interaction. In this paper, we consider a generalization of this formalism, the Partial Order Input/Output Automata (POIOA), in which each transition is associated with a partially ordered set of inputs and outputs. This new formalism allows the specification...

Use-cases have been identified as good inputs to generate test cases and oracles at requirement level. To have an automated generation, information is missing from use cases, such as the exact inputs of the system, and the sequential constraints between the use cases. The contribution of this paper is then two-fold. First we propose a contract language for PF functional requirements expressed a...

Barrel-related circuits in the somatosensory cortex of rodents process vibrissal information conveyed through the lemniscal pathway. Yet, the origin of vibrissal input to interbarrrel regions (septa) remains an unsettled issue. A recurring proposal that never received conclusive experimental support is that septa-related circuits process paralemniscal inputs conveyed through the posterior group...

We analyze the pattern formation behaviour of a high-dimensional SelfOrganizing-Map-model for the competitive projection of ON-center-type and OFF-center-type inputs to a common map layer. We mathematically show, and numerically con rm that even isotropic stimuli can drive the development of oriented receptive elds and an orientation map in this model. This result provides an important missing ...

In recent years, deep neural networks are used mainly as discriminators of multimodal learning. We should have large amounts of labeled data for training them, but obtaining such data is difficult because it requires much labor to label inputs. Therefore, semi-supervised learning, which improves the discriminator performance using unlabeled data, is important. Among semi-supervised learning, me...

An Input/Output Automaton is an automaton with a finite number of states where each transition is associated with a single inpuf or output interaction. In [1], we introduced a new formalism, in which each transition is associated with a bipartite partially ordered set made of concurrent inputs followed by concurrent outputs. In this paper, we generalize this model to Partial Order Input/Output ...