GenSBI delivers JAX-native implementations of generative SBI methods with transformer backbones and reports near-ideal calibration scores on standard benchmarks.
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A simulation-based inference method with Gaussian process emulators trained on 1300 kilonova simulations recovers parameters accurately and rapidly while avoiding MCMC biases from likelihood misspecification.
Embedding selection mechanisms into generative simulators enables amortized Bayesian inference to produce debiased, well-calibrated posteriors without tractable likelihoods.
citing papers explorer
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GenSBI: Generative Methods for Simulation-Based Inference in JAX
GenSBI delivers JAX-native implementations of generative SBI methods with transformer backbones and reports near-ideal calibration scores on standard benchmarks.
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Rapid and robust simulation-based inference for kilonovae
A simulation-based inference method with Gaussian process emulators trained on 1300 kilonova simulations recovers parameters accurately and rapidly while avoiding MCMC biases from likelihood misspecification.
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Overcoming Selection Bias in Statistical Studies With Amortized Bayesian Inference
Embedding selection mechanisms into generative simulators enables amortized Bayesian inference to produce debiased, well-calibrated posteriors without tractable likelihoods.