Research map / Probabilistic and scientific modeling / Variational and generative sampling
On the Limitations of Multimodal VAEs
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use modality sub-sampling in place of a unimodal VAE | MMVAE and MoPoE-VAE · PolyMNIST, Translated-PolyMNIST, and CUB images | FID | Hurt |
| Remove modality sub-sampling | MVAE · PolyMNIST, Translated-PolyMNIST, and CUB images | FID | Helped |
| Add modalities (ablation) | MMVAE and MoPoE-VAE · PolyMNIST and Translated-PolyMNIST | FID | Hurt |
| Add modalities (ablation) | MVAE · Translated-PolyMNIST | FID | Hurt |
| Use MMVAE or MoPoE-VAE instead of MVAE | Multimodal VAEs · PolyMNIST | leave-one-out coherence | Helped |
| Increase beta (ablation) | MVAE · PolyMNIST | leave-one-out coherence | Helped |
| Use Translated-PolyMNIST, where shared information cannot be predicted in expectation across modalities | MMVAE, MoPoE-VAE, and MVAE · Translated-PolyMNIST | generative coherence | Hurt |
| Conditionally generate images from captions on real-image CUB | MMVAE, MoPoE-VAE, and MVAE · CUB | generative coherence | Hurt |
Closest papers by meaning
- MMVAE+: Enhancing the Generative Quality of Multimodal VAEs without Compromises (ICLR 2023 · similarity 0.94)
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- Unity by Diversity: Improved Representation Learning for Multimodal VAEs (NeurIPS 2024 · similarity 0.91)
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