Table 2.

FC-VAE model architecture.

LayersaEncoder layersDecoder layers
For each expert1FCFC(μ,σ)FCFC
2FCFCFC(μ,σ)FCFCFC
3FCFCFCFC(μ,σ)FCFCFCFC
LayersaEncoder layersDecoder layers
For each expert1FCFC(μ,σ)FCFC
2FCFCFC(μ,σ)FCFCFC
3FCFCFCFC(μ,σ)FCFCFCFC

For FC-VAEs based on product of experts, the number of layers in each expert (modality-specific encoder–decoder) differ across each FC-VAE variant. Taking FC-VAE (L1) as an example, for each expert, the encoder contains one fully connected layer in addition to one that outputs mean and log-variance parameters, and the decoder consists of two fully connected layers.

a

Number of encoding layers [excluding FC(μ,σ)].

Table 2.

FC-VAE model architecture.

LayersaEncoder layersDecoder layers
For each expert1FCFC(μ,σ)FCFC
2FCFCFC(μ,σ)FCFCFC
3FCFCFCFC(μ,σ)FCFCFCFC
LayersaEncoder layersDecoder layers
For each expert1FCFC(μ,σ)FCFC
2FCFCFC(μ,σ)FCFCFC
3FCFCFCFC(μ,σ)FCFCFCFC

For FC-VAEs based on product of experts, the number of layers in each expert (modality-specific encoder–decoder) differ across each FC-VAE variant. Taking FC-VAE (L1) as an example, for each expert, the encoder contains one fully connected layer in addition to one that outputs mean and log-variance parameters, and the decoder consists of two fully connected layers.

a

Number of encoding layers [excluding FC(μ,σ)].

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