Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Gaussian process regression for astronomical time series
S Aigrain, D Foreman-Mackey - Annual Review of Astronomy …, 2023 - annualreviews.org
The past two decades have seen a major expansion in the availability, size, and precision of
time-domain data sets in astronomy. Owing to their unique combination of flexibility …
time-domain data sets in astronomy. Owing to their unique combination of flexibility …
Machine learning in electron microscopy for advanced nanocharacterization: current developments, available tools and future outlook
In the last few years, electron microscopy has experienced a new methodological paradigm
aimed to fix the bottlenecks and overcome the challenges of its analytical workflow. Machine …
aimed to fix the bottlenecks and overcome the challenges of its analytical workflow. Machine …
The Dawes Review 10: The impact of deep learning for the analysis of galaxy surveys
F Lanusse - Publications of the Astronomical Society of Australia, 2023 - cambridge.org
The amount and complexity of data delivered by modern galaxy surveys has been steadily
increasing over the past years. New facilities will soon provide imaging and spectra of …
increasing over the past years. New facilities will soon provide imaging and spectra of …
Machine learning for observational cosmology
An array of large observational programs using ground-based and space-borne telescopes
is planned in the next decade. The forthcoming wide-field sky surveys are expected to …
is planned in the next decade. The forthcoming wide-field sky surveys are expected to …
First impressions: early-time classification of supernovae using host-galaxy information and shallow learning
Substantial effort has been devoted to the characterization of transient phenomena from
photometric information. Automated approaches to this problem have taken advantage of …
photometric information. Automated approaches to this problem have taken advantage of …
Searching for changing-state agns in massive data sets. i. applying deep learning and anomaly-detection techniques to find agns with anomalous variability behaviors
The classic classification scheme for active galactic nuclei (AGNs) was recently challenged
by the discovery of the so-called changing-state (changing-look) AGNs. The physical …
by the discovery of the so-called changing-state (changing-look) AGNs. The physical …
Parsnip: Generative models of transient light curves with physics-enabled deep learning
K Boone - The Astronomical Journal, 2021 - iopscience.iop.org
We present a novel method to produce empirical generative models of all kinds of
astronomical transients from data sets of unlabeled light curves. Our hybrid model, which we …
astronomical transients from data sets of unlabeled light curves. Our hybrid model, which we …
Deep attention-based supernovae classification of multiband light curves
In astronomical surveys, such as the Zwicky Transient Facility, supernovae (SNe) are
relatively uncommon objects compared to other classes of variable events. Along with this …
relatively uncommon objects compared to other classes of variable events. Along with this …
The ROAD to discovery: Machine-learning-driven anomaly detection in radio astronomy spectrograms
Context. As radio telescopes increase in sensitivity and flexibility, so do their complexity and
data rates. For this reason, automated system health management approaches are …
data rates. For this reason, automated system health management approaches are …
Inferencing Progenitor and Explosion Properties of Evolving Core-collapse Supernovae from Zwicky Transient Facility Light Curves
We analyze a sample of 45 Type II supernovae from the Zwicky Transient Facility public
survey using a grid of hydrodynamical models in order to assess whether theoretically …
survey using a grid of hydrodynamical models in order to assess whether theoretically …