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Found 6 papers, 5 papers with code
Sequencing seismograms: A panoptic view of scattering in the core-mantle boundary region
In nearly half of the diffracting waveforms, we detected seismic waves scattered by three-dimensional structures near the core-mantle boundary.
Extracting the main trend in a dataset: the Sequencer algorithm
However, some are challenging to detect as they may be expressed in complex manners.
Machine Learning in Astronomy: a practical overview
This document summarizes the topics of supervised and unsupervised learning algorithms presented during the school, and provides practical information on the application of such tools to astronomical datasets.
Instrumentation and Methods for Astrophysics
Black hole mass estimation for Active Galactic Nuclei from a new angle
The scaling relations between supermassive black holes and their host galaxy properties are of fundamental importance in the context black hole-host galaxy co-evolution throughout cosmic time.
Astrophysics of Galaxies
Probabilistic Random Forest: A machine learning algorithm for noisy datasets
Apart from improving the prediction accuracy in noisy datasets, the PRF naturally copes with missing values in the data, and outperforms RF when applied to a dataset with different noise characteristics in the training and test sets, suggesting that it can be used for Transfer Learning.
The weirdest SDSS galaxies: results from an outlier detection algorithm
We find objects which have extreme emission line ratios and abnormally strong absorption lines, objects with unusual continua, including extremely reddened galaxies.
Astrophysics of Galaxies
