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Disentangled VAE

CircleCI

Replicating DeepMind's papers "β-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework" and "Understanding disentangling in β-VAE"

2D shape disentaglement

Result by changing latent Z from -3.0 to 3.0 with γ=100.0 and C=20.0

Latent variables with small variances seem extracting "x", "y", "rotation" and "scale" parameters.

(This experiment is using DeepMind's dsprite data set.)

Z Image Parameter Variance
z0 0.9216
z1 0.9216
z2 Rotation 0.0011
z3 Rotation? 0.0038
z4 Pos X 0.0002
z5 0.9384
z6 Scale? 0.0004
z7 0.8991
z8 0.9483
z9 Pos Y 0.0004

Reconstruction result

Left: original Right: reconstructed image