On the approximation of posterior laws in compound loss models by conditional Wasserstein GANs

arXiv:2608.27229 · q-fin.RM, stat.ML · Submitted 2026-08-27 · Read on arXiv

q-fin.RM, stat.ML

Submitted: 2026-08-27

Updated: 2026-08-27

Terminology

Calibration — 11× in this paper · explained in 7 episodes
Bayesian Inference — 7× in this paper · explained in 5 episodes
Wasserstein Distance — 7× in this paper · explained in 4 episodes
Benchmark — 6× in this paper · explained in 2 episodes
Variational Bayes — 6× in this paper · explained in 2 episodes
Accuracy — 4× in this paper · explained in 1 episode
Activation Function — 3× in this paper · explained in 1 episode
Adam — 3× in this paper · explained in 2 episodes
Mode Collapse — 2× in this paper · explained in 2 episodes
Optimal Transport — 2× in this paper · explained in 5 episodes
Simulation-based Inference — 2× in this paper · explained in 2 episodes
Amortization — 1× in this paper · explained in 1 episode
Bayesian Framework — 1× in this paper · explained in 3 episodes
Copula — 1× in this paper · explained in 2 episodes
Exchangeability — 1× in this paper · explained in 2 episodes
Generalization — 1× in this paper · explained in 13 episodes
Hilbert Space — 1× in this paper · explained in 2 episodes
Inverse Problem — 1× in this paper · explained in 2 episodes
Nash Equilibrium — 1× in this paper · explained in 2 episodes
Objective Function — 1× in this paper · explained in 2 episodes

Sources

Validating Bayesian Inference Algorithms with Simulation-Based Calibration

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