Open wangemm opened 4 years ago
@wangemm There are a number of parameters that can influence results. For example, the initialization of weights (line 51-71 in utils.py), and the width of the latent space distribution (line 81 in utils.py). The original author suggested for the latter a small value of like 0.15 for this, but I chose 0.75 during testing cause it avoided mode collapse on my system.
Furthermore, I did not include a classification model as in the author's original paper and repo. I assume you're using the architectures described in the paper...
@zhampel Thanks! I`ll try.
@wangemm have you achieved the paper results?
@TanmDL No,I can`t achieve the paper results.
code example 2 error,Please ask about the possible reasons
The paper proposes a modified backpropagation algorithm, but why is it not reflected in the code?
I have been running the code with the default params on MNIST, and using enc_zc_logits as the clustering results. And get the results: acc 0.56843 nmi 0.50773 ari 0.35441 fmi 0.44946