Multimodal missing data in healthcare: A comprehensive review and future directions
The rapid advancement in healthcare data collection technologies and the importance of
using multimodal data for accurate diagnosis leads to a surge in multimodal data …
using multimodal data for accurate diagnosis leads to a surge in multimodal data …
On Disentanglement of Asymmetrical Knowledge Transfer for Modality-Task Agnostic Federated Learning
There has been growing concern regarding data privacy during the development and
deployment of Multimodal Foundation Models for Artificial General Intelligence (AGI), while …
deployment of Multimodal Foundation Models for Artificial General Intelligence (AGI), while …
Disentangling genotype and environment specific latent features for improved trait prediction using a compositional autoencoder
In plant breeding and genetics, predictive models traditionally rely on compact
representations of high-dimensional data, often using methods like Principal Component …
representations of high-dimensional data, often using methods like Principal Component …