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Mar 8, 2024 · We show improved learned latent representations and imputation of missing data modalities compared to existing methods.
May 27, 2024 · We propose a novel multimodal VAE that learns from data using a data-dependent mixture-of-experts prior for soft-sharing of information between modalities.
In this paper, we introduce the MM-VAMP VAE, a novel multimodal VAE formulation using a shoft sharing of information between modalities.
Mar 8, 2024 · Variational Autoencoders for multimodal data hold promise for many tasks in data analysis, such as representation learning, conditional ...
In this work, we show that a better latent representation can be obtained by replacing these hard constraints with a soft constraint. We propose ...
Improved Representation Learning in Multimodal VAEs - NASA/ADS
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Variational Autoencoders for multimodal data hold promise for many tasks in data analysis, such as representation learning, conditional generation, ...
Jun 2, 2024 · This paper presents a new approach called "Unity by Diversity" (UbD) that improves representation learning in multimodal Variational ...
Unity by Diversity: Improved Representation Learning in Multimodal VAEs. Published in arxiv, 2024. We propose a novel multimodal VAE that enables multimodal ...
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What is multimodal representation learning?
TM Sutter, JE Vogt. Neurips Workshop on Bayesian Deep Learning, 2021. 2, 2021. Unity by Diversity: Improved Representation Learning in Multimodal VAEs. TM ...
Figure 1 for Unity by Diversity: Improved Representation Learning in Multimodal VAEs. Abstract:Variational Autoencoders for multimodal data hold promise for ...