Results for "belief divergence"

Updated belief after observing data.

Belief before observing data.

Gradients grow too large, causing divergence; mitigated by clipping, normalization, careful init.

Measures divergence between true and predicted probability distributions.

Gradually increasing learning rate at training start to avoid divergence.

Measures how one probability distribution diverges from another.