PTED: A multi-dimensional two-sample test for scientific inference and generative machine learning

arXiv:2609.38388 · astro-ph.IM, physics.data-an, stat.ML · Submitted 2026-09-29 · Read on arXiv

astro-ph.IM, physics.data-an, stat.ML

Submitted: 2026-09-29

Updated: 2026-09-29

Code: https://github.com/ConnorStoneAstro/pted_tests

Terminology

• Generative Model — 11× in this paper · explained in 2 episodes
• Generative Models — 7× in this paper · explained in 3 episodes
• Probability Integral Transform — 5× in this paper
• Adam — 4× in this paper · explained in 2 episodes
• Bayesian Inference — 4× in this paper · explained in 5 episodes
• Core — 4× in this paper · explained in 2 episodes
• Wasserstein Distance — 3× in this paper · explained in 4 episodes
• Calibration — 2× in this paper · explained in 7 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Simulation-based Inference — 2× in this paper · explained in 2 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Hallucination — 1× in this paper · explained in 4 episodes
• Highest Posterior Density — 1× in this paper
• Nash Equilibrium — 1× in this paper · explained in 2 episodes
• Radial Basis Function — 1× in this paper

Sources

• Validating Bayesian Inference Algorithms with Simulation-Based Calibration
• Permutation p-values should never be zero: calculating exact p-values when permutations are randomly drawn
• PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation
• Score-Based Generative Modeling through Stochastic Differential Equations
• MIRA: A Score for Conditional Distribution Accuracy and Model Comparison
• PyTorch: An Imperative Style, High-Performance Deep Learning Library

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