probly.train.evidential.torch.normal_wishart_log_prob

probly.train.evidential.torch.normal_wishart_log_prob(m: Tensor, l_precision: Tensor, kappa: Tensor, nu: Tensor, mu_k: Tensor, sigma2_k: Tensor) → Tensor[source]

Compute simplified univariate Normal-Wishart log-likelihood.

Parameters:

  • m (Tensor) – Prior mean parameter.

  • l_precision (Tensor) – Precision (> 0), formerly L.

  • kappa (Tensor) – Strength parameter (> 0).

  • nu (Tensor) – Degrees of freedom (> 2).

  • mu_k (Tensor) – Sample mean from ensemble.

  • sigma2_k (Tensor) – Sample variance from ensemble.

Returns:

Log-likelihood under the Normal-Wishart model.

Return type:

Tensor