Moreover, we utilize amino acid replacement matrices for the diffusion forward process, encoding the biologically meaningful prior knowledge of amino acids from their spatial and sequential neighbors as well as themselves, which reduces the sampling space of the generative process.

Amongst those functions, the simplest are single-index modelsf(x) = ϕ(x θ), where the labels are generated by an arbitrary non-linear scalar link functionϕ applied to an unknown one-dimensional projectionθ of the input data.

In online multiclass classification a learner has to repeatedly predict the label that corresponds to a feature vector. Algorithms in this setting have a wide range of applications ranging from predicting the outcomes ofsport matches torecommender systems.