We present a lightweight system to extract, store and manage metadata and provenance information of common artifacts in machine learning (ML) experiments: datasets, models, predictions, evaluations and training runs. Our system accelerates users in their ML workflow, and provides a basis for comparability and repeatability of ML experiments. We achieve this by tracking the lineage of produced a...

Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g., multivariate analysis of activation images or resting-state time series. Supervised learning is typically used in decoding or encoding settings to relate brain images to behavioral or clinical observations, while unsupervised lea...

5 While random forest algorithm has been found to be prominent for various 6 classification tasks, like many other machine learning algorithms it requires 7 a number of parameters to be tuned to ensure better performance. Even 8 though the strong influence of different parameters on random forest is 9 evident, an attempt to systematically optimize these parameters is rare. 10 Common techniques ...

uncontrolled hypertension is well- known to give rise to systemic complications involving multiple central organs. artherosclerosis leads to damage of the retinal vessels wall, contributing to venous stasis, thrombosis and finally, occlusion. retinal vein occlusions compromise vision through development of ischaemic maculopathy, macular oedema, and rubeotic glaucoma. laser photocoagulation rema...

Abstract Scientists investigating the thermal properties of black holes rely heavily on theoretical and non-empirical tools, such as mathematical derivations, analogue experiments thought experiments. Although use derivations in context hole physics has recently received a great deal attention among philosophers science, (TEs) that been almost completely neglected. In this paper, we will start ...