You can view a deep neural network as a graphical model, but here, the CPDs are not probabilistic but are deterministic. Consider for example that the input to a neuron is $\vec{x}$ and the output of the neuron is y
. In the CPD for this neuron we have, $p(\vec{x},y)=1$, and $p(\vec{x},\hat{y})=0$ for $\hat{y}\neq y$. Refer to the section 10.2.3 of Deep Learning Book for more details.
↧
Answer by Hossein for Are Neural Nets a Special Case Of Graphical Models?
↧