In the life sciences, short time series with high dimensional entries are becoming more and more popular such as spectrometric data or gene expression profiles taken over time. Data characteristics rule out classical time series analysis due to the few time points, and they prevent a simple vectorial treatment due to the high dimensionality. In this contribution, we successfully use the generat...

Previous studies report that acquired prosopagnosia is frequently associated with topographic disorientation. Whether this is associated with a specific anatomic subtype of prosopagnosia, how frequently it is seen with the developmental variant, and what specific topographic function is impaired to account for this problem are not known. We studied ten subjects with acquired prosopagnosia from ...

Dimensionality reduction is required to produce visualizations of high dimensional data. In this framework, one of the most straightforward approaches to visualising high dimensional data is based on reducing complexity and applying linear projections while tumbling the projection axes in a defined sequence which generates a Grand Tour of the data. We propose using smooth nonlinear topographic ...

The SOM has several beneficial features which make it a useful method for data mining. One of the most important features is the ability to preserve the topology in the projection. There are several measures that can be used to quantify the goodness of the map in order to obtain the optimal projection, including the average quantization error and many topological errors. Many researches have st...

Topographic maps in visual processing areas maintain the spatial order of the visual world. Molecular cues and neuronal activity both play critical roles in map formation, but their interaction remains unclear. Here, we demonstrate that when molecular- and activity-dependent cues are rendered nearly equal in force, they drive topographic mapping stochastically. The functional and anatomical rep...

this study was done to investigation forest cover changes in the mazandaran province in topographic zones. for doing that in the first matched topographic zones and land-use map. after that distribution of forest cover was investigated in plain, lowland, middle land and high land. forest cover changes analyzed in a period of 132 years since the beginning of the destructive activities in the for...

Collaborative clustering is a recent field of Machine Learning that shows similarities with both ensemble learning and transfer learning. Using a two-step approach where different clustering algorithms first process data individually and then exchange their information and results with a goal of mutual improvement, collaborative clustering has shown promising performances when trying to have se...

The Lattice of a Self-Organizing Map can be considered as an ”elastic network” that is fitted into the data space. The network is non-linear but locally the non-linear surface can be approximated by a linear hyperplane. This property could be utilized to visualize the direction of the network at any location of the map, by fitting a surface to the model vectors of the neighbors of a node and vi...