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Found 4 papers, 0 papers with code
Re-Envisioning Numerical Information Field Theory (NIFTy.re): A Library for Gaussian Processes and Variational Inference
Imaging is the process of transforming noisy, incomplete data into a space that humans can interpret.
Sparse Kernel Gaussian Processes through Iterative Charted Refinement (ICR)
Gaussian Processes (GPs) are highly expressive, probabilistic models.
Bayesian decomposition of the Galactic multi-frequency sky using probabilistic autoencoders
The three most significant feature maps encode astrophysical components: (1) The dense interstellar medium (ISM), (2) the hot and dilute regions of the ISM and (3) the CMB.
Instrumentation and Methods for Astrophysics High Energy Astrophysical Phenomena Data Analysis, Statistics and Probability
Optimal Belief Approximation
The loss function that is obtained in the derivation is equal to the Kullback-Leibler divergence when normalized.
