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Found 4 papers, 3 papers with code
Neural Methods for Amortised Parameter Inference
Simulation-based methods for making statistical inference have evolved dramatically over the past 50 years, keeping pace with technological advancements.
Neural Bayes Estimators for Irregular Spatial Data using Graph Neural Networks
Neural Bayes estimators are neural networks that approximate Bayes estimators in a fast and likelihood-free manner.
Neural Bayes estimators for censored inference with peaks-over-threshold models
Making inference with spatial extremal dependence models can be computationally burdensome since they involve intractable and/or censored likelihoods.
Likelihood-Free Parameter Estimation with Neural Bayes Estimators
Neural point estimators are neural networks that map data to parameter point estimates.
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