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stat.ML2025
CoLT: The conditional localization test for assessing the accuracy of neural posterior estimates
Tianyu Chen, Vansh Bansal, James G. Scott
We consider the problem of validating whether a neural posterior estimate \( q(θ\mid x) \) is an accurate approximation to the true, unknown true posterior \( p(θ\mid x) \). Existi…
stat.ML2025
Conformal C2ST: Turning weak classifiers into strong two-sample tests
Vansh Bansal, Tianyu Chen, James G. Scott
The two-sample testing problem, a fundamental task in statistics and machine learning, seeks to determine whether two sets of samples, drawn from underlying distributions and $…
stat.ML2024
Conditional diffusions for amortized neural posterior estimation
Tianyu Chen, Vansh Bansal, James G. Scott
Neural posterior estimation (NPE), a simulation-based computational approach for Bayesian inference, has shown great success in approximating complex posterior distributions. Exist…