Description

Question 1: VAEs on 2D Data [20pt]
(a) [10pt] Data from a Full Covariance Gaussian
Final Full -ELBO: 4.4388, Recon Loss: 2.7630, KL Loss: 1.6758 (Dataset 1)

(a) Training curve (b) Samples with Noise (c) Samples without Noise
Figure 1: Results for Dataset 1
Final Full -ELBO: FILL, Recon Loss: FILL, KL Loss: FILL (Dataset 2)

(a) Training curve (b) Samples with Noise (c) Samples without Noise
Figure 2: Results for Dataset 2
(b) [10pt] Data from a Diagonal Gaussian
Final Full -ELBO: 4.4213, Recon Loss: 4.4094, KL Loss: 0.0119 (Dataset 1)

(a) Training curve (b) Samples with Noise (c) Samples without Noise
Figure 3: Results for Dataset 1
Final Full -ELBO: FILL, Recon Loss: FILL, KL Loss: FILL (Dataset 2)

(a) Training curve (b) Samples with Noise (c) Samples without Noise
Figure 4: Results for Dataset 2
Answer: Your answer to the reflection portion of part (b) reflection here (replace this text)
Question 2: VAEs on Images [40pt]
(a) [20pt] VAE
Final Full -ELBO: 104.0417, Recon Loss: 79.3798, KL Loss: 24.6620 (Dataset 1)

(a) Training Curve (b) Samples

(c) Reconstructions (d) Interpolations
Figure 5: Results for Dataset 1
Final Full -ELBO: FILL, Recon Loss: FILL, KL Loss: FILL (Dataset 2)

(a) Training Curve (b) Samples

(c) Reconstructions (d) Interpolations
Figure 6: Results for Dataset 2
(b) [20pt] VAE with AF Prior
Final Full -ELBO: 102.5659, Recon Loss: 80.2548, KL Loss: 22.3111 (Dataset 1)

(a) Training Curve (b) Samples

(c) Reconstructions (d) Interpolations
Figure 7: Results for Dataset 1
Final Full -ELBO: FILL, Recon Loss: FILL, KL Loss: FILL (Dataset 2)

(a) Training Curve (b) Samples

(c) Reconstructions (d) Interpolations
Figure 8: Results for Dataset 2
Question 3: VQ-VAE [40pt]
Final VQ-VAE Test Loss: 0.0286, PixelCNN Prior Test Los: 1.9440 (Dataset 1)

(a) VQ-VAE Training Curve (b) PixelCNN Prior Training Curve

(c) Samples (d) Reconstructions
Figure 9: Results for Dataset 1
Final VQ-VAE Test Loss: FILL, PixelCNN Prior Test Los: FILL (Dataset 2)

(a) VQ-VAE Training Curve (b) PixelCNN Prior Training Curve

(c) Samples (d) Reconstructions
Figure 10: Results for Dataset 1
Question 4: Bonus [10pt]
1. [5pt] Improving VQ-VAE Results
Final VQ-VAE Test Loss: FILL, PixelCNN Prior Test Los: FILL

(a) VQ-VAE Training Curve (b) PixelCNN Prior Training Curve

(c) Samples (d) Reconstructions
Figure 11: Results for CIFAR10
2. [5pt] PixelVAE
Final Full -ELBO: FILL, Recon Loss: FILL, KL Loss: FILL

(a) Training curve (b) Samples (c) Reconstructions
Figure 12: Results for MNIST