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stat.ML2026
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.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 \( p(θ\mid x) \). Exis…
stat.ML2025
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…