Samplers#
JESTER provides modern Bayesian sampling algorithms optimized for EOS inference with JAX acceleration. All samplers support GPU hardware and automatic differentiation.
Sequential Monte Carlo (SMC)#
Adaptive tempering with Random Walk or NUTS kernels. Recommended default.
Nested Sampling (NS-AW)#
Acceptance Walk variant for evidence computation and parameter estimation.
FlowMC#
Normalizing flow-enhanced MCMC for efficient exploration of complex posteriors.