dodiscover.ci.kernel_utils.f_divergence_score#
- dodiscover.ci.kernel_utils.f_divergence_score(y_stat_q, y_stat_p)[source]#
Compute f-divergence upper bound on KL-divergence.
See definition 4 in [1], where the function is reversed to give an upper-bound for the sake of gradient descent.
The f-divergence bound gives an upper bound on KL-divergence:
- Parameters:
- y_stat_qarray_like of shape (n_samples_q,)
Samples from the distribution Q, the variational class.
- y_stat_p: array_like of shape (n_samples_p,)
Samples from the distribution P, the joint distribution.
- Returns:
- f_div
float
The f-divergence score.
- f_div