Search Results for author:
Found 6 papers, 4 papers with code
Informative regularization for a multi-layer perceptron RR Lyrae classifier under data shift
Consequently, we propose a scalable and easily adaptable approach based on an informative regularization and an ad-hoc training procedure to mitigate the shift problem during the training of a multi-layer perceptron for RR Lyrae classification.
Bayesian Reconstruction of Fourier Pairs
Our aim is to address the lack of a principled treatment of data acquired indistinctly in the temporal and frequency domains in a way that is robust to missing or noisy observations, and that at the same time models uncertainty effectively.
MPCC: Matching Priors and Conditionals for Clustering
Our experiments show that adding a learnable prior and augmenting the number of encoder updates improve the quality of the generated samples, obtaining an inception score of 9. 49 $\pm$ 0. 15 and improving the Fr\'echet inception distance over the state of the art by a 46. 9% in CIFAR10.
An Information Theory Approach on Deciding Spectroscopic Follow Ups
We propose a methodology in a probabilistic setting that determines a-priory which objects are worth taking spectrum to obtain better insights, where we focus 'insight' as the type of the object (classification).
Robust period estimation using mutual information for multi-band light curves in the synoptic survey era
Robust and efficient methods that can aggregate data from multidimensional sparsely-sampled time series are needed.
Instrumentation and Methods for Astrophysics Information Theory Information Theory
Computational Intelligence Challenges and Applications on Large-Scale Astronomical Time Series Databases
In this article we present an overview of machine learning and computational intelligence applications to TDA.
