Hi, I was wondering how I should go about implementing a SBN in torch? (references 14 and 7 in https://arxiv.org/pdf/1506.05254v3.pdf 44, for example)
You guys put in something for stochastic nodes, with the RL example here, https://github.com/pytorch/examples/blob/master/reinforcement_learning/reinforce.py 14
But the neural network itself isn’t actually stochastic - just that the output is sampled. I get that this generates the next state (input to the network) and so in a way it’s like a stochastic neural network - but each stochastic node needs a reward right? Would I just use the same ‘reward’ for each stochastic neuron?
Cheers.