J oint e nergy-based m odels (JEM), proposed in 2020 by Grathwohl et al., allow any classifier with softmax output to be interpreted as energy-based model. The key observation is that such a classifier is trained to predict the conditional probability p θ θ ( y | x ) = e f → → θ θ ( x ) [ y ] ∑ ∑ j = 1 K e f → → θ θ ( x ) [ j ] for y = 1 , … … , K and f → → θ θ = ( f 1 , … … , f K ) ∈ ∈ R K , where f → → θ θ ( x ) [ y ] is the y-th index of the logits f → → corresponding to class y. Without any change to the logits it was proposed to reinterpret the logits to describe a joint probability density: