Data mining and machine learning in astronomy
NM Ball, RJ Brunner - International Journal of Modern Physics D, 2010 - World Scientific
We review the current state of data mining and machine learning in astronomy. Data Mining
can have a somewhat mixed connotation from the point of view of a researcher in this field. If …
can have a somewhat mixed connotation from the point of view of a researcher in this field. If …
Non-Gaussian information from weak lensing data via deep learning
Weak lensing maps contain information beyond two-point statistics on small scales. Much
recent work has tried to extract this information through a range of different observables or …
recent work has tried to extract this information through a range of different observables or …
Astronomy in the big data era
Y Zhang, Y Zhao - Data Science Journal, 2015 - account.datascience.codata.org
The fields of Astrostatistics and Astroinformatics are vital for dealing with the big data issues
now faced by astronomy. Like other disciplines in the big data era, astronomy has many V …
now faced by astronomy. Like other disciplines in the big data era, astronomy has many V …
SkyNet: an efficient and robust neural network training tool for machine learning in astronomy
We present the first public release of our generic neural network training algorithm, called
SkyNet. This efficient and robust machine learning tool is able to train large and deep feed …
SkyNet. This efficient and robust machine learning tool is able to train large and deep feed …
Accurate prediction of X-ray pulse properties from a free-electron laser using machine learning
A Sanchez-Gonzalez, P Micaelli, C Olivier… - Nature …, 2017 - nature.com
Free-electron lasers providing ultra-short high-brightness pulses of X-ray radiation have
great potential for a wide impact on science, and are a critical element for unravelling the …
great potential for a wide impact on science, and are a critical element for unravelling the …
Rock thin sections identification based on improved squeeze-and-Excitation Networks model
Rock thin section recognition provides geological information, which is crucial in petroleum
geology, exploration, and mining research as a kind of fundamental work. Although many …
geology, exploration, and mining research as a kind of fundamental work. Although many …
Supervised detection of exoplanets in high-contrast imaging sequences
CAG Gonzalez, O Absil… - Astronomy & …, 2018 - aanda.org
Context. Post-processing algorithms play a key role in pushing the detection limits of high-
contrast imaging (HCI) instruments. State-of-the-art image processing approaches for HCI …
contrast imaging (HCI) instruments. State-of-the-art image processing approaches for HCI …
Data science applied to carbon materials: synthesis, characterization, and applications
A Morelos‐Gomez, M Terrones… - Advanced Theory and …, 2022 - Wiley Online Library
Data science has been rapidly developed and implemented in diverse scientific and
technological fields over the past decade, to accelerate new knowledge generation and …
technological fields over the past decade, to accelerate new knowledge generation and …
QSO photometric redshifts using machine learning and neural networks
The scientific value of the next generation of large continuum surveys would be greatly
increased if the redshifts of the newly detected sources could be rapidly and reliably …
increased if the redshifts of the newly detected sources could be rapidly and reliably …
[HTML][HTML] Artificial neural network modeling of the conformable fractional isothermal gas spheres
The isothermal gas sphere is a particular type of Lane-Emden equation and is used widely
to model many problems in astrophysics, like the formation of stars, star clusters and …
to model many problems in astrophysics, like the formation of stars, star clusters and …