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ICLR 2020: Yann LeCun and Energy-Based Models
Machine Learning Street Talk (MLST)
How to Normalize an Energy Function Into a Probability Distribution
There is a way of transforming an energy function into a probability, and this is one of the things that yan talks about. The way he does it is by normalizing, using this gip distribution. If if you normalize over the integrals a, over the domainfof your wires, you can turn any energy a function into a Probablistic model. So yes, there's a connection. I would say every probalistic model is an energy based model, and every energy based model can be turned into a probablistic model by normalizing future of machine running anai is self supervised.
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