Search Results - "Adversarial variational autoencoder"

Controllable Blind AC FDIA via Physics-Informed Extrapolative AVAE

Authors: Siliang Zhao Wuman Luo Qin Shu et al.

Source: Sensors ; Volume 25 ; Issue 3 ; Pages: 943

Subject Terms: controllable false data injection attack, AC state estimation, physics informed, data driven, extrapolative adversarial variational autoencoder

File Description: application/pdf

Relation: Sensor Networks; https://dx.doi.org/10.3390/s25030943

Availability: https://doi.org/10.3390/s25030943

Adversarial Variational Autoencoders to Extend and Improve Generative Model

Authors: Nguyen, Loc Abdalla, Hassan I. Amer, Ali A.

Source: All Works

Subject Terms: Generative artificial intelligence, Variational autoencoder, Generative adversarial network, Deep generative model, Adversarial variational autoencoder, Computer Sciences

File Description: application/pdf

Relation: https://zuscholars.zu.ac.ae/works/6860; https://zuscholars.zu.ac.ae/context/works/article/7897/viewcontent/375.pdf

Availability: https://zuscholars.zu.ac.ae/works/6860
https://doi.org/10.5772/acrt.20240003
https://zuscholars.zu.ac.ae/context/works/article/7897/viewcontent/375.pdf

Advanced computational analysis of neuroimaging data for brain injury identification and decoding behavior

Contributors: Salsabilian, Shiva (author) Najafizadeh, Laleh (chair) Chen, Yingying YC (member) et al.

Subject Terms: Electrical engineering, Biomedical engineering, Computer science, Adversarial variational autoencoder, Applied machine learning, Cross-subject transfer learning, Mild traumatic brain injury identification, Neural decoding of behavior, Widefield calcium imaging

File Description: 148 pages : illustrations; application/pdf

Relation: Rutgers University Electronic Theses and Dissertations; ETD; School of Graduate Studies Electronic Theses and Dissertations; rucore10001600001; http://dissertations.umi.com/gsnb.rutgers:12324

Availability: http://dissertations.umi.com/gsnb.rutgers:12324

An LSTM-based adversarial variational autoencoder framework for self-supervised neural decoding of behavioral choices.

Authors: Salsabilian S Lee C Margolis D et al.

Source: Journal of neural engineering [J Neural Eng] 2024 Jul 09; Vol. 21 (3). Date of Electronic Publication: 2024 Jul 09.

Publication Type: Journal Article; Research Support, U.S. Gov't, Non-P.H.S.

Journal Info: Publisher: Institute of Physics Pub Country of Publication: England NLM ID: 101217933 Publication Model: Electronic Cited Medium: Internet ISSN: 1741-2552 (Electronic) Linking ISSN: 17412552 NLM ISO Abbreviation: J Neural Eng Subsets: MEDLINE

MeSH Terms: Choice Behavior*/physiology, Animals ; Mice ; Neural Networks, Computer ; Mice, Transgenic ; Supervised Machine Learning ; Unsupervised Machine Learning