Transylvanian Machine Learning Summer School

Our institute supported, as partner, the first edition of the Transylvanian Machine Learning Summer School (TMLSS), which took place in Cluj, Transylvania, Romania in July 16-22, 2018. The focus of school was on Deep Learning and Reinforcement Learning. The school was organized by machine learning researchers from DeepMind (Răzvan Pașcanu, Viorica Pătrăucean), Romanian Institute of Science and Technology (Luigi Malagò, Răzvan Florian), and McGill University & DeepMind (Doina Precup).

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A new class of spike train metrics

Cătălin Rusu and Răzvan Florian have developed a series of several new metrics for quantifying the differences between spike trains. The new metrics are inspired by the Pompeiu-Hausdorff distance.

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Finding attractors of continuous-time systems by parameter switching

RIST’s Marius F. Danca has found that if the control parameter p, of a continuous-time nonlinear system belonging to a large class of systems, is switched within a set of chosen values in a deterministic or even random manner, while the underlying model is numerically integrated, the obtained attractor is a numerical approximation of one of the existing attractors of the considered system.

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Visualizing how the brain encodes information

The institute’s scientists have developed a special visualization technique for how multiple neurons fire spikes together to encode information, by representing the identity of firing patterns of multiple neurons with color sequences.

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