The methods and techniques used across SBI4GALEV, with how often each was mentioned in talk transcripts and slides, and the talks that covered it. Extracted and counted on-box.
Generative models that learn to reverse a gradual noising process to sample distributions.
Process of modeling galaxy physical properties from their multi-wavelength flux.
Amortized inference method that learns to map observations directly to the posterior distribution.
Gradient-based MCMC sampling method efficient for high-dimensional parameter spaces.
A kernel-based distance metric used to compare two probability distributions.
Method that learns an emulator for the likelihood function to perform Bayesian inference.
Generative models that transform simple distributions into complex ones via invertible mappings.
A Bayesian sampling method used for evidence calculation and multimodal posteriors.
Validation technique to check if inferred posteriors are statistically consistent with the truth.
Computational technique to automatically calculate derivatives of a function.
Inference method that estimates the likelihood ratio to recover the posterior.
Inference performed using simulators when the analytical likelihood is intractable.