I am trying to train a VAE for anomaly detection. I chose one architecture from this Github repository and I adjusted the input and output to match what I need. In my case, the input (and hence the output) are a 12D vector. I tried several sizes for the latent space, but, for some reason, it's not training. From the beginning, the KL loss in almost zero (around 1e-10), while the reconstruction loss (MSE for Gaussian distribution) is around 1, and they basically vary around these values without learning anything further.
Are there any general tips for troubleshooting a VAE (I never trained one before)?
I am pretty sure that the code is right and the data for sure has a background and signal (the ratio is 10:1), so I am not really sure what I am doing wrong.