Results 111 to 120 of about 30,104 (177)
Machine Learning Approaches for Supernovae Classification
In this chapter, authors have discussed few machine learning techniques and their application to perform the supernovae classification. Supernovae has various types, mainly categorized into two important types.
Kakoli Bora, Surbhi Agrawal, Swati Routh
core +1 more source
Superluminous supernovae: diverse rise times explain diverse spectra. [PDF]
Nicholl M.
europepmc +1 more source
LIGO Core-Collapse Supernova Detection Using Convolutional Neural Networks. [PDF]
Pan Z +3 more
europepmc +1 more source
Dynamical dark energy in light of the DESI DR2 baryonic acoustic oscillations measurements. [PDF]
Gu G +59 more
europepmc +1 more source
Strongly lensed supernovae: lessons learned. [PDF]
Goobar A +2 more
europepmc +1 more source
Developing aluminum molecular plating for neutron-induced reaction target fabrication. [PDF]
Essenmacher SD +4 more
europepmc +1 more source
Everyone wants something better than ΛCDM. [PDF]
Turner MS.
europepmc +1 more source
A persistent influence of supernovae on biodiversity over the Phanerozoic. [PDF]
Svensmark H.
europepmc +1 more source
Could dark energy be changing over time? [PDF]
Mann A.
europepmc +1 more source
StarWhisper Telescope: an AI framework for automating end-to-end astronomical observations. [PDF]
Wang C +33 more
europepmc +1 more source

