[Discussion] Epistemic NNs: Marginal vs Joint Log Loss

I was recently reading the following paper that introduces an architecture called “Epistemic Neural Networks”: [https://arxiv.org/pdf/2107.08924.pdf](https://arxiv.org/pdf/2107.08924.pdf). The proposed architecture achieves high quality joint probability predictions at lower computational cost than other methods (e.g. ensembles). The paper measures the quality of joint predictions in terms of the “joint log loss” (as opposed to the marginal log loss, which as far as I can tell is the traditional log likelihood expression). Does anyone know how this joint log loss term is computed? …

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