Results 281 to 290 of about 4,772,239 (326)

ICVAE: Interpretable Conditional Variational Autoencoder for De Novo Molecular Design. [PDF]

Int J Mol Sci
Fan X, Fang S, Li Z, Ji H, Yue M, Li J, Ren X.   +6 more
europepmc   +1 more source

ECG Sensor Design Assessment with Variational Autoencoder-Based Digital Watermarking. [PDF]

Sensors (Basel)
Hsu CY, Chang CY, Chen YC, Wu J, Chen ST.   +4 more
europepmc   +1 more source

SNPmanifold: detecting single-cell clonality and lineages from single-nucleotide variants using binomial variational autoencoder. [PDF]

Genome Biol
Chung HM, Huang Y.
europepmc   +1 more source

Novel cancer subtyping method guided by tumor-normal sample in latent space of transcriptomic variational autoencoder. [PDF]

Sci Rep
Wang H, Zhang Y, Zhang D, Luo M.
europepmc   +1 more source

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Anomaly Detection Using LSTM-Based Variational Autoencoder in Unsupervised Data in Power Grid

IEEE Systems Journal, 2023
This article proposes a deep generative model for anomaly detection in unsupervised power grid data. One-class classifier-based methods suffer from performance degradation when training data contain anomalous samples.
Dibyajyoti Guha, Rajdeep Chatterjee, B. Sikdar   +2 more
semanticscholar   +1 more source

A Novel Model for Ship Trajectory Anomaly Detection Based on Gaussian Mixture Variational Autoencoder

IEEE Transactions on Vehicular Technology, 2023
The use of traditional methods in anomaly detection of multi-class ship trajectories showed some limitations in terms of robustness and learning ability of trajectory features. In view of this, an anomaly detection model for ship trajectory data based on
Lei Xie, Tao Guo, Jiliang Chang, C. Wan, Xinyuan Hu, Yang Yang, Changkui Ou   +6 more
semanticscholar   +1 more source

Modelling Cellular Perturbations with the Sparse Additive Mechanism Shift Variational Autoencoder

Neural Information Processing Systems, 2023
Generative models of observations under interventions have been a vibrant topic of interest across machine learning and the sciences in recent years. For example, in drug discovery, there is a need to model the effects of diverse interventions on cells ...
Michael D. Bereket, Theofanis Karaletsos
semanticscholar   +1 more source

Conditional Variational Autoencoder for Sign Language Translation with Cross-Modal Alignment

AAAI Conference on Artificial Intelligence, 2023
Sign language translation (SLT) aims to convert continuous sign language videos into textual sentences. As a typical multi-modal task, there exists an inherent modality gap between sign language videos and spoken language text, which makes the cross ...
Rui Zhao, Liang Zhang, Biao Fu, Cong Hu, Jinsong Su, Yi-Dong Chen   +5 more
semanticscholar   +1 more source

Conditional Variational Autoencoder Informed Probabilistic Wind Power Curve Modeling

IEEE Transactions on Sustainable Energy, 2023
In this article, a conditional variational autoencoder based method is proposed for the probabilistic wind power curve modeling task. To advance the modeling performance, the latent random variable is introduced to characterize underlying weather and ...
Zhong Zheng, Luo-Xiao Yang, Zi-Jun Zhang
semanticscholar   +1 more source

Latent Diffusion Model without Variational Autoencoder

arXiv.org
Recent progress in diffusion-based visual generation has largely relied on latent diffusion models with variational autoencoders (VAEs). While effective for high-fidelity synthesis, this VAE+diffusion paradigm suffers from limited training efficiency ...
Ming-Lei Shi, Haolin Wang, Wenzhao Zheng, Ziyang Yuan, Xiaoshi Wu, Xintao Wang, Peng-Fei Wan, Jie Zhou, Ji-Wen Lu   +8 more
semanticscholar   +1 more source