Results 51 to 60 of about 4,772,239 (326)
A Quaternion-Valued Variational Autoencoder [PDF]
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021 Accepted for publication at the 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Grassucci E., Comminiello D., Uncini A.
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Tumour growth prediction of follow‐up lung cancer via conditional recurrent variational autoencoder
IET Image Processing, 2020 The prediction of lung tumour growth is the key to early treatment of lung cancer. However, the lack of intuitive and clear judgments about the future development of the tumour often leads patients to miss the best treatment opportunities.
Ning Xiao +4 more
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Three Variations on Variational Autoencoders
CoRR, 2022 21 pages. This version, v2, has added an explicit evaluation of our VAE A variational encoder.
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MVAE: Multimodal Variational Autoencoder for Fake News Detection
The Web Conference, 2019 In recent times, fake news and misinformation have had a disruptive and adverse impact on our lives. Given the prominence of microblogging networks as a source of news for most individuals, fake news now spreads at a faster pace and has a more profound ...
Dhruv Khattar +3 more
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SC-VAE: Sparse coding-based variational autoencoder with learned ISTA [PDF]
Pattern Recognition, 2023 Learning rich data representations from unlabeled data is a key challenge towards applying deep learning algorithms in downstream tasks. Several variants of variational autoencoders (VAEs) have been proposed to learn compact data representations by ...
Pan Xiao +5 more
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Disentangling Variational Autoencoders
CoRR, 2022 A variational autoencoder (VAE) is a probabilistic machine learning framework for posterior inference that projects an input set of high-dimensional data to a lower-dimensional, latent space. The latent space learned with a VAE offers exciting opportunities to develop new data-driven design processes in creative disciplines, in particular, to automate ...
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Suggestion and invention of recipes using bi-directional LSTMs-based frameworks
SN Applied Sciences, 2021 Choosing which recipe to eat and which recipe to avoid isn’t that simple for anyone. It takes strenuous efforts and a lot of time for people to calculate the number of calories and P.H level of the dish.
Sai Nikhil Rao Gona, Himamsu Marellapudi
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Application of Variational AutoEncoder (VAE) Model and Image Processing Approaches in Game Design
Italian National Conference on Sensors, 2023 In recent decades, the Variational AutoEncoder (VAE) model has shown good potential and capability in image generation and dimensionality reduction. The combination of VAE and various machine learning frameworks has also worked effectively in different ...
Hugo Wai Leung Mak +2 more
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Longitudinal Variational Autoencoder
CoRR, 2020 Peer ...
Ramchandran, Siddharth +4 more
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Cognitive Workload Estimation Using Variational Autoencoder and Attention-Based Deep Model
IEEE Transactions on Cognitive and Developmental Systems, 2023 The estimation of cognitive workload using electroencephalogram (EEG) is an emerging research area. However, due to poor spatial resolution issues, features obtained from EEG signals often lead to poor classification results.
Debashis Das Chakladar +3 more
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