Comments (5)
Just spoke with Hao Wu who wrote this code, it's a result of occasional bad proposal step. He will look into details and revise it. Thanks for bringing it up.
from stochastic_normalizing_flows.
Thanks for your timely response. But according to the paper the mean and covariance of LangevinVAE looks not so bad, not sure it is occasional bad proposal step. I try different random seed, and all reports NLL around 200.
Thanks for you again your insightful paper, it is really a nice work.
from stochastic_normalizing_flows.
@franknoe
def energy_1(self, x, y):
return (x**2).sum(axis=2, keepdims=True) / 2 - self.G.conditional_log_likelihood(x, y).sum(axis=2, keepdims=True)
The bug is because lambda is passed instead of y and conditional log likelihood is calculated using the lambda value.
from stochastic_normalizing_flows.
thank you! Could you send a PR?
from stochastic_normalizing_flows.
Hi there, Iām just following the bread crumbs on this and Iām a bit confused as to the status of the Langevin VAE result in Table 3. Is the result in the paper correct? How should I reproduce it, please? Thanks
from stochastic_normalizing_flows.
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