Amortized neural posterior estimation via simulation-based inference delivers 82x faster inference than MCMC for heat exchanger fouling and leakage diagnosis while maintaining comparable accuracy on synthetic data.
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Bayesian neural posterior estimation recovers marginal generation costs from market schedules with credible intervals but shows start-up costs are largely unidentifiable from schedules alone.
Simulation-based inference uses neural networks trained on simulations to enable parameter inference in cosmology and astrophysics where traditional likelihood calculations are intractable.
citing papers explorer
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Fast Bayesian equipment condition monitoring via simulation based inference: applications to heat exchanger health
Amortized neural posterior estimation via simulation-based inference delivers 82x faster inference than MCMC for heat exchanger fouling and leakage diagnosis while maintaining comparable accuracy on synthetic data.
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Bayesian Inference for Estimating Generation Costs in Electricity Markets
Bayesian neural posterior estimation recovers marginal generation costs from market schedules with credible intervals but shows start-up costs are largely unidentifiable from schedules alone.
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Machine Learning Techniques for Astrophysics and Cosmology: Simulation-Based Inference
Simulation-based inference uses neural networks trained on simulations to enable parameter inference in cosmology and astrophysics where traditional likelihood calculations are intractable.