Data-Targeted Prior Distribution for Variational AutoEncoder by Nissrine Akkari, Fabien Casenave, Thomas Daniel, David Ryckelynck

Subjects: Get full text

Informative Language Encoding by Variational Autoencoders Using Transformer by Changwon Ok, Geonseok Lee, Kichun Lee

Subjects: Get full text

Variational Autoencoder With Optimizing Gaussian Mixture Model Priors by Chunsheng Guo, Jialuo Zhou, Huahua Chen, Na Ying, Jianwu Zhang, Di Zhou

Subjects: “…Variational autoencoder…”
Get full text

Optimizing Few-Shot Learning Based on Variational Autoencoders by Ruoqi Wei, Ausif Mahmood

Subjects: Get full text

Dirichlet Process Prior for Student’s t Graph Variational Autoencoders by Yuexuan Zhao, Jing Huang

Get full text

Sequential Variational Autoencoder with Adversarial Classifier for Video Disentanglement by Takeshi Haga, Hiroshi Kera, Kazuhiko Kawamoto

Subjects: Get full text

Benchmarking variational AutoEncoders on cancer transcriptomics data. by Mostafa Eltager, Tamim Abdelaal, Mohammed Charrout, Ahmed Mahfouz, Marcel J T Reinders, Stavros Makrodimitris

“…Deep generative models, such as variational autoencoders (VAE), have gained increasing attention in computational biology due to their ability to capture complex data manifolds which subsequently can be used to achieve better performance in downstream tasks, such as cancer type prediction or subtyping of cancer. …”
Get full text

Data Generation with Variational Autoencoders and Generative Adversarial Networks by Daniil Devyatkin, Ivan Trenev

“…The improvement of variational autoencoders (VAEs) is discussed. Practical implementation is performed using the Python programming language and the Keras framework. …”
Get full text

Junction tree variational autoencoder for molecular graph generation by Jin, Wengong, Barzilay, Regina, Jaakkola, Tommi

“…Our junction tree variational autoencoder generates molecular graphs in two phases, by first generating a tree-structured scaffold over chemical substructures, and then combining them into a molecule with a graph message passing network. …”
Get full text

Towards a theoretical understanding of the robustness of variational autoencoders by Camuto, A, Willetts, M, Roberts, S, Holmes, C, Rainforth, T

“…We make inroads into understanding the robustness of Variational Autoencoders (VAEs) to adversarial attacks and other input perturbations. …”

Predicting Aging of Brain Metabolic Topography Using Variational Autoencoder by Hongyoon Choi, Hyejin Kang, Dong Soo Lee, Dong Soo Lee, Dong Soo Lee, The Alzheimer's Disease Neuroimaging Initiative

Subjects: Get full text

Coupled VAE: Improved Accuracy and Robustness of a Variational Autoencoder by Shichen Cao, Jingjing Li, Kenric P. Nelson, Mark A. Kon

“…We present a coupled variational autoencoder (VAE) method, which improves the accuracy and robustness of the model representation of handwritten numeral images. …”
Get full text

Generation of geometric interpolations of building types with deep variational autoencoders by Jaime de Miguel Rodríguez, Maria Eugenia Villafañe, Luka Piškorec, Fernando Sancho Caparrini

Subjects: Get full text

Cutting anomaly detection in end-milling by multimodal variational autoencoder by Kazuya ODA, Haruhiko SUWA, Koji MURAKAMI

Subjects: Get full text

Predicting chemotherapy response using a variational autoencoder approach by Qi Wei, Stephen A. Ramsey

“…Recently, multiple studies have established the utility of a deep neural network approach, the variational autoencoder (VAE), for generating meaningful latent features from original data. …”
Get full text

Variational Autoencoder for Image-Based Augmentation of Eye-Tracking Data by Mahmoud Elbattah, Colm Loughnane, Jean-Luc Guérin, Romuald Carette, Federica Cilia, Gilles Dequen

Subjects: Get full text

Loop closure detection of visual SLAM based on variational autoencoder by Shibin Song, Fengjie Yu, Xiaojie Jiang, Jie Zhu, Weihao Cheng, Xiao Fang

Subjects: Get full text

Exploring Factor Structures Using Variational Autoencoder in Personality Research by Yufei Huang, Yufei Huang, Jianqiu Zhang

“…In this paper, we investigate if an effective deep learning tool for factor extraction, the Variational Autoencoder (VAE), can be applied to explore the factor structure of a set of personality variables. …”
Get full text

Balancing Reconstruction Error and Kullback-Leibler Divergence in Variational Autoencoders by Andrea Asperti, Matteo Trentin

Subjects: Get full text

Functional Subspace Variational Autoencoder for Domain-Adaptive Fault Diagnosis by Tan Li, Che-Heng Fung, Him-Ting Wong, Tak-Lam Chan, Haibo Hu

Subjects: Get full text