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Learn Z0 ≡ shape and Z1 ≡ size. Latent dimension Z0 is passed to the classifier for shape and latent dimension Z1 is passed to the classifier for size. The user-uttered labels for shape are square, heart and for size are small, big. All images which can not be described by the user-uttered labels—ellipse for shape and medium for size—are given an unknown ground truth label.
Full Model (Alpha = 1, Beta = 30, Gamma = 10000)
Full Model (Alpha = 1, Beta = 30, Gamma = 10000)
Scatter plot of the validation data points for concept group 0 (shape) over Z0 (x axis) and Z1 (y axis)
Scatter plot of the validation data points for concept group 1 (size) over Z0 (x axis) and Z1 (y axis)
Per-concept group confusion matrix for classifying every image part of the customised dSprites-based dataset. The labels are consistent with the the description at the top of the page. The statistics from the matrices are used to calculate the reported F1 scores in the paper.
Cosine similarity diagrams for the labels from concept group 0 (heart, square) and concept group 1 (big, small). The average entropy of the distributions of normalised cosine values for the white cells, for each label, is reported in the paper. The value below each component from the PCA analysis represents the eigen value for that component.
Classifier Network (Alpha = 0, Beta = 30, Gamma = 10000)
Classifier Network (Alpha = 0, Beta = 30, Gamma = 10000)
Scatter plot of the validation data points for concept group 0 (shape) over Z0 (x axis) and Z1 (y axis)
Scatter plot of the validation data points for concept group 1 (size) over Z0 (x axis) and Z1 (y axis)
Per-concept group confusion matrix for classifying every image part of the customised dSprites-based dataset. The labels are consistent with the the description at the top of the page. The statistics from the matrices are used to calculate the reported F1 scores in the paper.
Cosine similarity diagrams for the labels from concept group 0 (heart, square) and concept group 1 (big, small). The average entropy of the distributions of normalised cosine values for the white cells, for each label, is reported in the paper. The value below each component from the PCA analysis represents the eigen value for that component.
Beta-VAE (Alpha = 1, Beta = 30, Gamma = 0)
Beta-VAE (Alpha = 1, Beta = 30, Gamma = 0)
Scatter plot of the validation data points for concept group 0 (shape) over Z0 (x axis) and Z1 (y axis)
Scatter plot of the validation data points for concept group 1 (size) over Z0 (x axis) and Z1 (y axis).
Per-concept group confusion matrix for classifying every image part of the customised dSprites-based dataset. The labels are consistent with the the description at the top of the page. The statistics from the matrices are used to calculate the reported F1 scores in the paper.
Cosine similarity diagrams for the labels from concept group 0 (heart, square) and concept group 1 (big, small). The average entropy of the distributions of normalised cosine values for the white cells, for each label, is reported in the paper. The value below each component from the PCA analysis represents the eigen value for that component.
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