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Gaussian Approximation Potentials for iron from extended first-principles dat...
Interatomic potentials are often necessary to describe complex realistic systems that would be too costly to study from first-principles. Commonly, interatomic potentials are... -
Benchmark data for: Machine Learning for geospatial vector data classification
Benchmark data for paper "Deep Learning for Classification Tasks on Geospatial Vector Polygons". Core of the data is in the six numpy zip files. Each numpy zip contains the... -
Data publication: Mineral quantification at deposit scale using drill-core hy...
We present a semi-automated workflow for large scale interpretation of Hyperspectral data, founded on a novel approach of mineral mapping based on a supervised dictionary... -
Data publication: Learning-based systems for assessing hazard places of conta...
The codes and data for the paper "Learning-based systems for assessing hazard places of contagious diseases and diagnosing patient possibility" -
3-D seismic interpretation with deep learning: a set of Python tutorials
Here we are sharing our code, tutorials and examples used to interpret geological structures (e.g. faults, salt bodies and horizones) in 2-D and/or 3-D seismic reflection data... -
ClassifyStorms - an automated classifier for geomagnetic storm drivers based ...
The software package “ClassifyStorms” version 1.0.1 performs a classification of geomagnetic storms according to their interplanetary driving mechanisms based exclusively on...