all AI news
VAE: CIFAR-10 & PyTorch - loss not improving
Jan. 10, 2022, 9:40 a.m. | /u/grid_world
Deep Learning www.reddit.com
I have implemented a Variational Autoencoder using Conv-6 CNN (VGG-* family) as the encoder and decoder with CIFAR-10 in PyTorch. You can refer to the full code here.
The problem is that the total loss (= reconstruction loss + KL-divergence loss) doesn't improve. Also, the log-variance is almost 0 indicating further that the multivariate Gaussians being mapped in the latent space is not happening as expected, since the log variance should have values between say -4 to +3, etc. …
!-->More from www.reddit.com / Deep Learning
How LLMs are trained? A simple guide to understand LLM Training
1 day, 3 hours ago |
www.reddit.com
What is the efficient way of learning ML?
1 day, 4 hours ago |
www.reddit.com
How can I truly learn to code the models, not just understand them?
3 days, 15 hours ago |
www.reddit.com
How does gradient descent work in random forest
3 days, 16 hours ago |
www.reddit.com
Prerequisites for jumping into transformers?
3 days, 18 hours ago |
www.reddit.com
Jobs in AI, ML, Big Data
Software Engineer for AI Training Data (School Specific)
@ G2i Inc | Remote
Software Engineer for AI Training Data (Python)
@ G2i Inc | Remote
Software Engineer for AI Training Data (Tier 2)
@ G2i Inc | Remote
Data Engineer
@ Lemon.io | Remote: Europe, LATAM, Canada, UK, Asia, Oceania
Artificial Intelligence – Bioinformatic Expert
@ University of Texas Medical Branch | Galveston, TX
Lead Developer (AI)
@ Cere Network | San Francisco, US