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Found 6 papers, 0 papers with code
Transient Classification in low SNR Gravitational Wave data using Deep Learning
We also use unsupervised models such as Total variation, Principal Component Analysis, Support Vector Machine, Wavelet decomposition or Random Forests for feature extraction and noise reduction and then study the results obtained by RNN-LSTM and deep CNN for classifying the transients in low-SNR signals.
Human eye inspired log-polar pre-processing for neural networks
A key point in this paper is that the CNN does not need to be trained to identify rotation or scaling permutations; rather it is the log-polar pre-processing step that converts the image into a format that allows the CNN to handle rotation and scaling permutations.
CMB-GAN: Fast Simulations of Cosmic Microwave background anisotropy maps using Deep Learning
We train our deep generative model to learn the complex distribution of CMB maps and efficiently generate new sets of CMB data in the form of 2D patches of anisotropy maps without losing much accuracy.
Baryon density extraction and isotropy analysis of Cosmic Microwave Background using a multilayer perceptron
We correlate the baryon density obtained from the power spectrum of CMB temperature maps with the corresponding map and form the dataset for training the neural network model.
Cosmology and Nongalactic Astrophysics
ExGate: Externally Controlled Gating for Feature-based Attention in Artificial Neural Networks
Perceptual capabilities of artificial systems have come a long way since the advent of deep learning.
A Dictionary Approach to Identifying Transient RFI
Transient (impulsive) RFI is particularly difficult to identify.
