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Found 3 papers, 2 papers with code
Platt-Bin: Efficient Posterior Calibrated Training for NLP Classifiers
Modern NLP classifiers are known to return uncalibrated estimations of class posteriors.
Adaptive Annealed Importance Sampling with Constant Rate Progress
This algorithm relies on a sequence of interpolating distributions bridging the target to an initial tractable distribution such as the well-known geometric mean path of unnormalized distributions which is assumed to be suboptimal in general.
Optimization of Annealed Importance Sampling Hyperparameters
Annealed Importance Sampling (AIS) is a popular algorithm used to estimates the intractable marginal likelihood of deep generative models.
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