Výsledky vyhledávání - "Graph Variational Autoencoder"

A Generative Framework for Predictive Modeling of Multiple Chronic Conditions Using Graph Variational Autoencoder and Bandit-Optimized Graph Neural Network

Autoři: Julian Carvajal Rico Adel Alaeddini Syed Hasib Akhter Faruqui a další

Zdroj: IEEE Journal of Biomedical and Health Informatics. :1-14

Témata: FOS: Computer and information sciences, Computer Science - Machine Learning, Machine Learning (cs.LG)

Přístupová URL adresa: http://arxiv.org/abs/2409.13671

BiAtt-GVAE: Molecular design for specific target via graph variational autoencoder based on bi-channel interactive attention network

Autoři: Mei Ma Xiujuan Lei

Zdroj: IEEE Transactions on Computational Biology and Bioinformatics. :1-12

VHGAE: Drug-Target Interaction Prediction Model Based on Heterogeneous Graph Variational Autoencoder

Autoři: Chen Zhang Jiaqi Sun Linlin Xing a další

Zdroj: Interdisciplinary Sciences: Computational Life Sciences.

Using Multi-Encoder Semi-Implicit Graph Variational Autoencoder to Analyze Single-Cell RNA Sequencing Data

Autoři: Shengwen Tian Cunmei Ji Jiancheng Ni a další

Zdroj: IEEE/ACM Transactions on Computational Biology and Bioinformatics. 21:2280-2291

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/39255084

Transformer and graph variational autoencoder to identify microenvironments: A deep learning protocol for spatial transcriptomics

Autoři: Karla Paniagua Yufei Huang Shou-jiang Gao a další

Zdroj: STAR Protocols, Vol 6, Iss 4, Pp 104206- (2025)

Témata: Bioinformatics, Sequence analysis, Single Cell, Cancer, Genomics, Gene Expression, Science (General), Q1-390

Popis souboru: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2666166725006124; https://doaj.org/toc/2666-1667

Přístupová URL adresa: https://doaj.org/article/d4aacf3200f84f91ac76d46ecb731e3e

Adversarial regularize graph variational autoencoder based on encoder optimization strategy

Autoři: Jin Dai Yanhui Peng Guoyin Wang a další

Zdroj: Artificial Intelligence Review. 58

A Fault Monitoring Algorithm for Process Industries Based on Graph Variational Autoencoder基于图变分自编码器的过程工业故障监测算法

Autoři: Xiaochen Hao Xin Chen Libin Wei a další

Enhancing Gas Turbine Fault Diagnosis Using a Multi-Scale Dilated Graph Variational Autoencoder Model

Autoři: Zhang Kun Li Hongren Wang Xin a další

Zdroj: IEEE Access, Vol 12, Pp 104818-104832 (2024)

Témata: noise robustness, Gas turbine, 0202 electrical engineering, electronic engineering, information engineering, MG-VAE, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, fault diagnosis, 01 natural sciences, TK1-9971, 0104 chemical sciences

Přístupová URL adresa: https://doaj.org/article/c986c7c9e0e34b09bbf948eb168f8205

piRNA-disease association prediction based on multi-channel graph variational autoencoder

Autoři: Wei Sun Chang Guo Jing Wan a další

Zdroj: PeerJ Computer Science, Vol 10, p e2216 (2024)

Témata: piRNA-disease association prediction, Graph variational autoencoder, Graph convolution network, Homogeneous similarity networks, Multi channel, Electronic computers. Computer science, QA75.5-76.95

Popis souboru: electronic resource

Relation: https://peerj.com/articles/cs-2216.pdf; https://peerj.com/articles/cs-2216/; https://doaj.org/toc/2376-5992

Přístupová URL adresa: https://doaj.org/article/f83e553177a94c6aad107f2cae0baa56

Transformer graph variational autoencoder for generative molecular design.

Autoři: Nguyen T Karolak A

Zdroj: Biophysical journal [Biophys J] 2025 Nov 18; Vol. 124 (22), pp. 3867-3875. Date of Electronic Publication: 2025 Jan 30.

Způsob vydávání: Journal Article

Informace o časopise: Publisher: Cell Press Country of Publication: United States NLM ID: 0370626 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1542-0086 (Electronic) Linking ISSN: 00063495 NLM ISO Abbreviation: Biophys J Subsets: MEDLINE

Výrazy ze slovníku MeSH: Neural Networks, Computer* , Drug Design*, Autoencoder

MAGVA: An Open-Set Fault Diagnosis Model Based on Multi-Hop Attentive Graph Variational Autoencoder for Autonomous Vehicles

Autoři: Rao Fu Yuanguo Bi Guangjie Han a další

Zdroj: IEEE Transactions on Intelligent Transportation Systems. 24:14873-14889

Enhancing Graph Variational Autoencoder for Short Text Topic Modeling with Mutual Information Maximization

Autoři: Yuhang Ge Xuegang Hu

Zdroj: 2022 IEEE International Conference on Knowledge Graph (ICKG). :64-70

Témata: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 01 natural sciences, 0105 earth and related environmental sciences

A Generative Framework for Predictive Modeling of Multiple Chronic Conditions Using Graph Variational Autoencoder and Bandit-Optimized Graph Neural Network

Autoři: Rico, Julian Carvajal Alaeddini, Adel Faruqui, Syed Hasib Akhter a další

Témata: Computer Science - Machine Learning, text

URL: http://arxiv.org/abs/2409.13671

BPS2025 - Molecular design with generative AI: A transformer graph variational autoencoder approach

Autoři: Trieu Nguyen Aleksandra M. Karolak

Zdroj: Biophysical Journal. 124:321a

Disentangled Representation of Longitudinal Β-Amyloid for AD Via Sequential Graph Variational Autoencoder with Supervision

Autoři: Fan Yang Guorong Wu Won Hwa Kim

Zdroj: 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI). :1-5

Témata: 03 medical and health sciences, 0302 clinical medicine, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Malware detection framework based on graph variational autoencoder extracted embeddings from API-call graphs

Autoři: Hakan Gunduz

Zdroj: PeerJ Computer Science, Vol 8, p e988 (2022)

Témata: Malware detection, Recursive Feature Elimination, Graph Variational Autoencoder, Graph embeddings, API-call graphs, Electronic computers. Computer science, QA75.5-76.95

Popis souboru: electronic resource

Relation: https://peerj.com/articles/cs-988.pdf; https://peerj.com/articles/cs-988/; https://doaj.org/toc/2376-5992

Přístupová URL adresa: https://doaj.org/article/0f80ca246aec48eb95ec0d5b168998e5

Fragment‐based deep molecular generation using hierarchical chemical graph representation and multi‐resolution graph variational autoencoder

Autoři: Zhenxiang Gao Xinyu Wang Blake Blumenfeld Gaines a další

Zdroj: Molecular Informatics. 42

Témata: Models, Molecular, 0301 basic medicine, 0303 health sciences, 03 medical and health sciences, Drug Discovery, Neural Networks, Computer

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/36764926

NF-VGA: Incorporating Normalizing Flows into Graph Variational Autoencoder for Embedding Attribute Networks

Autoři: Pengfei Jiao Ziyang Liu Di Jin a další

Zdroj: 2020 IEEE International Conference on Data Mining (ICDM). :1244-1249

Témata: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Přístupová URL adresa: https://dblp.uni-trier.de/db/conf/icdm/icdm2020.html#ShanJJLLH20

CR-LSO: Convex Neural Architecture Optimization in the Latent Space of Graph Variational Autoencoder with Input Convex Neural Networks

Autoři: Rao, Xuan Zhao, Bo Yi, Xiaosong a další

Témata: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, text

URL: http://arxiv.org/abs/2211.05950

Genetic Constrained Graph Variational Autoencoder for COVID-19 Drug Discovery

Autoři: Cheng, Tianyue Fan, Tianchi Wang, Landi

Témata: Computer Science - Machine Learning, Quantitative Biology - Quantitative Methods, text

URL: http://arxiv.org/abs/2104.11674