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Found 4 papers, 3 papers with code
Parameter Inference for Weak Lensing using Gaussian Processes and MOPED
Much larger gains will come with future data, where with MOPED compression, the speed up can be up to a factor of $\sim 10^3$ when the common Limber approximation is used.
Cosmology and Nongalactic Astrophysics
Imbalance Learning for Variable Star Classification
In this work, we attempt to further improve hierarchical classification performance by applying 'data-level' approaches to directly augment the training data so that they better describe under-represented classes.
Comparing Multi-class, Binary and Hierarchical Machine Learning Classification schemes for variable stars
Upcoming synoptic surveys are set to generate an unprecedented amount of data.
Marginal Likelihoods from Monte Carlo Markov Chains
In this paper, we present a method for computing the marginal likelihood, also known as the model likelihood or Bayesian evidence, from Markov Chain Monte Carlo (MCMC), or other sampled posterior distributions.
Computation Cosmology and Nongalactic Astrophysics
