Scientific discovery in the age of artificial intelligence
Artificial intelligence (AI) is being increasingly integrated into scientific discovery to augment
and accelerate research, helping scientists to generate hypotheses, design experiments …
and accelerate research, helping scientists to generate hypotheses, design experiments …
Review of deep learning algorithms and architectures
A Shrestha, A Mahmood - IEEE access, 2019 - ieeexplore.ieee.org
Deep learning (DL) is playing an increasingly important role in our lives. It has already made
a huge impact in areas, such as cancer diagnosis, precision medicine, self-driving cars …
a huge impact in areas, such as cancer diagnosis, precision medicine, self-driving cars …
The zwicky transient facility: science objectives
Abstract The Zwicky Transient Facility (ZTF), a public–private enterprise, is a new time-
domain survey employing a dedicated camera on the Palomar 48-inch Schmidt telescope …
domain survey employing a dedicated camera on the Palomar 48-inch Schmidt telescope …
The automatic learning for the rapid classification of events (ALeRCE) alert broker
F Förster, G Cabrera-Vives… - The Astronomical …, 2021 - iopscience.iop.org
Abstract We introduce the Automatic Learning for the Rapid Classification of Events
(ALeRCE) broker, an astronomical alert broker designed to provide a rapid and self …
(ALeRCE) broker, an astronomical alert broker designed to provide a rapid and self …
Comprehensive electrocardiographic diagnosis based on deep learning
Cardiovascular disease (CVD) is the leading cause of death worldwide, and coronary artery
disease (CAD) is a major contributor. Early-stage CAD can progress if undiagnosed and left …
disease (CAD) is a major contributor. Early-stage CAD can progress if undiagnosed and left …
Agency plus automation: Designing artificial intelligence into interactive systems
J Heer - Proceedings of the National Academy of Sciences, 2019 - National Acad Sciences
Much contemporary rhetoric regards the prospects and pitfalls of using artificial intelligence
techniques to automate an increasing range of tasks, especially those once considered the …
techniques to automate an increasing range of tasks, especially those once considered the …
Alert classification for the ALeRCE broker system: The light curve classifier
P Sánchez-Sáez, I Reyes, C Valenzuela… - The Astronomical …, 2021 - iopscience.iop.org
We present the first version of the Automatic Learning for the Rapid Classification of Events
(ALeRCE) broker light curve classifier. ALeRCE is currently processing the Zwicky Transient …
(ALeRCE) broker light curve classifier. ALeRCE is currently processing the Zwicky Transient …
[HTML][HTML] Comparing the prediction performance, uncertainty quantification and extrapolation potential of regression kriging and random forest while accounting for soil …
B Takoutsing, GBM Heuvelink - Geoderma, 2022 - Elsevier
Geostatistics and machine learning have been extensively applied for modelling and
predicting the spatial distribution of continuous soil variables. In addition to providing …
predicting the spatial distribution of continuous soil variables. In addition to providing …
A review on big data based on deep neural network approaches
Big data analytics has become a significant trend for many businesses as a result of the
daily acquisition of enormous volumes of data. This information has been gathered because …
daily acquisition of enormous volumes of data. This information has been gathered because …
Surveying the reach and maturity of machine learning and artificial intelligence in astronomy
Abstract Machine learning (automated processes that learn by example in order to classify,
predict, discover, or generate new data) and artificial intelligence (methods by which a …
predict, discover, or generate new data) and artificial intelligence (methods by which a …