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Found 7 papers, 1 papers with code
Upper Bound of Real Log Canonical Threshold of Tensor Decomposition and its Application to Bayesian Inference
Tensor decomposition is now being used for data analysis, information compression, and knowledge recovery.
Deep Learning for Line Intensity Mapping Observations: Information Extraction from Noisy Maps
The trained cGANs successfully reconstruct H{\alpha} emission from galaxies at a target redshift from observed, noisy intensity maps.
Astrophysics of Galaxies Cosmology and Nongalactic Astrophysics
Noise reduction for weak lensing mass mapping: An application of generative adversarial networks to Subaru Hyper Suprime-Cam first-year data
We study the non-Gaussian information in denoised maps using one-point probability distribution functions (PDFs) and also perform matching analysis for positive peaks and massive clusters.
Denoising Weak Lensing Mass Maps with Deep Learning
Weak gravitational lensing is a powerful probe of the large-scale cosmic matter distribution.
Single-epoch supernova classification with deep convolutional neural networks
Our method first builds a convolutional neural network for estimating the luminance of supernovae from telescope images, and then constructs another neural network for the classification, where the estimated luminance and observation dates are used as features for classification.
Machine-learning Selection of Optical Transients in Subaru/Hyper Suprime-Cam Survey
We present an application of machine-learning (ML) techniques to source selection in the optical transient survey data with Hyper Suprime-Cam (HSC) on the Subaru telescope.
Instrumentation and Methods for Astrophysics
Simulating the joint evolution of quasars, galaxies and their large-scale distribution
The cold dark matter model has become the leading theoretical paradigm for the formation of structure in the Universe.
astro-ph
