SSDMM-VAE: variational multi-modal disentangled representation learning

Arnab Kumar Mondal; Ajay Sailopal; Parag Singla; Prathosh AP

doi:10.1007/s10489-022-03936-z

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SSDMM-VAE: variational multi-modal disentangled representation learning

Arnab Kumar Mondal Ajay Sailopal Parag Singla Prathosh AP

Year: 2022 Journal: Applied Intelligence Vol: 53 (7)Pages: 8467-8481 Publisher: Springer Science+Business Media

DOI: 10.1007/s10489-022-03936-z

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Keywords:

Computer science Inference Feature learning Artificial intelligence Machine learning Representation (politics) MNIST database Invariant (physics) Modal Autoencoder Latent variable Pattern recognition (psychology) Artificial neural network Mathematics

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Multimodal Machine Learning Applications

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Speech Recognition and Synthesis

Physical Sciences → Computer Science → Artificial Intelligence

Topic Modeling

Physical Sciences → Computer Science → Artificial Intelligence

SSDMM-VAE: variational multi-modal disentangled representation learning

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