AIDE: An algorithm for measuring the accuracy of probabilistic inference algorithms
Marco Cusumano-Towner, Vikash K. Mansinghka
–Neural Information Processing Systems
Approximate probabilistic inference algorithms are central to many fields. Examples include sequential Monte Carlo inference in robotics, variational inference in machine learning, and Markov chain Monte Carlo inference in statistics.
Neural Information Processing Systems
Nov-21-2025, 12:19:01 GMT
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