normal_wishart_log_prob

probly.losses.torch.normal_wishart_log_prob(m: Tensor, l_precision: Tensor, kappa: Tensor, nu: Tensor, mu_k: Tensor, sigma2_k: Tensor) → Tensor

Simplified Normal-Wishart log-likelihood based on [MCPG20].

Used by rpn_distillation_loss() for univariate ensemble distribution distillation with Regression Prior Networks.

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