Search Results - Graph Variational Autoencoder~

Multi-modal graph convolutional network for vessel trajectory prediction based on cooperative intention enhance using conditional variational autoencoder

Authors: Jiang, Junhao Zuo, Yi Li, Zhiyuan

Source: Reliability Engineering and System Safety. 267

Subject Terms: Graph convolutional network, Trajectory prediction, Cooperative intention constructor, Intelligent situational awareness systems, Conditional variational autoencoder, Multi-modal interaction extractor

Access URL: https://research.chalmers.se/publication/549377

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

Authors: Julian Carvajal Rico Adel Alaeddini Syed Hasib Akhter Faruqui et al.

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

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

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

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

Authors: Mei Ma Xiujuan Lei

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

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

Authors: Shengwen Tian Cunmei Ji Jiancheng Ni et al.

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

Access URL: https://pubmed.ncbi.nlm.nih.gov/39255084

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

Authors: Chen Zhang Jiaqi Sun Linlin Xing et al.

Source: Interdisciplinary Sciences: Computational Life Sciences.

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

Authors: Karla Paniagua Yufei Huang Shou-jiang Gao et al.

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

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

File Description: electronic resource

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

Access URL: https://doaj.org/article/d4aacf3200f84f91ac76d46ecb731e3e

Expanding Molecular Design with Graph Variational Autoencoders: A Comparative Study of Pair-Encoding and Character Tokenization

Authors: Trieu Nguyen Aleksandra Karolak

Identification of microbe–disease signed associations via multi-scale variational graph autoencoder based on signed message propagation

Authors: Huan Zhu Hongxia Hao Liang Yu

Source: BMC Biol
BMC Biology, Vol 22, Iss 1, Pp 1-15 (2024)

Subject Terms: 0301 basic medicine, 0303 health sciences, QH301-705.5, Microbiota, Computational Biology, 3. Good health, Variational graph autoencoder, 03 medical and health sciences, Signed message propagation, Microbe-disease association, Humans, Disease, Biology (General), Algorithms, XGBoost, Research Article

Access URL: https://pubmed.ncbi.nlm.nih.gov/39148051
https://doaj.org/article/dac9fc4571f045d086486c10341093e2

Transformer graph variational autoencoder for generative molecular design.

Authors: Nguyen T Karolak A

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

Publication Type: Journal Article

Journal Info: 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

MeSH Terms: Neural Networks, Computer* , Drug Design*, Autoencoder

A Case Study on Monolith to Microservices Decomposition with Variational Autoencoder-Based Graph Neural Network.

Authors: Maharjan, Rokin Sooksatra, Korn Cerny, Tomas et al.

Source: Future Internet. Jul2025, Vol. 17 Issue 7, p303. 19p.

Subject Terms: Graph neural networks, Clustering algorithms, Service-oriented architecture (Computer science), Probabilistic generative models, Software architecture, Mathematical decomposition

RGCVAE: relational graph conditioned variational autoencoder for molecule design

Authors: Davide Rigoni Nicolò Navarin Alessandro Sperduti

Source: Machine Learning. 114

Subject Terms: FOS: Computer and information sciences, Computer Science - Machine Learning, Artificial Intelligence (cs.AI), Quantitative Biology - Biomolecules, Computer Science - Artificial Intelligence, FOS: Biological sciences, Biomolecules (q-bio.BM), Machine Learning (cs.LG)

Access URL: http://arxiv.org/abs/2305.11699

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

Authors: Zhang Kun Li Hongren Wang Xin et al.

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

Subject Terms: 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

Access URL: https://doaj.org/article/c986c7c9e0e34b09bbf948eb168f8205

Learning particle dynamics: from diffusion to interactions

Authors: Fernández Fernández, Gabriel

Contributors: University/Department: Universitat Politècnica de Catalunya. Institut de Ciències Fotòniques

Thesis Advisors: Lewenstein, Maciej, Manzo, Carlo

Source: TDX (Tesis Doctorals en Xarxa)

Subject Terms: Unsupervised, Machine Learning, Variational Autoencoder, Feature Learning, Representation Learning, Autoregressive Model, Data Analysis, Knowledge Discovery, Interpretability, Biophysics, Anomalous Diffusion, Single Trajectory Characterization, Time Series, Stochastic Model, Brownian Motion, Fractional Brownian Motion, Scaled Brownian Motion, Confined Brownian Motion, Graph Neural Network, Lennard-Jones, Non-reciprocal Force, Àrees temàtiques de la UPC::Enginyeria de la telecomunicació, Àrees temàtiques de la UPC::Informàtica, 621.3 - Enginyeria elèctrica. Electrotècnia. Telecomunicacions, 004 - Informàtica, 577 - Bioquímica. Biologia molecular. Biofísica

File Description: application/pdf

Access URL: http://hdl.handle.net/10803/696076
https://dx.doi.org/10.5821/dissertation-2117-448803

Adversarial regularize graph variational autoencoder based on encoder optimization strategy

Authors: Jin Dai Yanhui Peng Guoyin Wang et al.

Source: 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

Authors: Xiaochen Hao Xin Chen Libin Wei et al.

Variational Type Graph Autoencoder for Denoising on Event Recommendation.

Authors: Zhang, Shuo Meng, Xiangwu Zhang, Yujie

Source: ACM Transactions on Information Systems. Jan2025, Vol. 43 Issue 1, p1-27. 27p.

Subject Terms: *Artificial intelligence, Autoencoder, Latent variables, Signal denoising, Random graphs

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

Authors: Wei Sun Chang Guo Jing Wan et al.

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

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

File Description: electronic resource

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

Access URL: https://doaj.org/article/f83e553177a94c6aad107f2cae0baa56

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

Authors: Rao Fu Yuanguo Bi Guangjie Han et al.

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

Text-Conditioned Graph Generation Using Discrete Graph Variational Autoencoders

Authors: Longland, Michael

Index Terms: Graph Generation, Graph Neural Networks, Deep Learning, anzsrc-for: 461103 Deep learning, master thesis, http://purl.org/coar/resource_type/c_bdcc

URL: http://hdl.handle.net/1959.4/103506
https://unsworks.unsw.edu.au/bitstreams/ff9fafdf-e349-4498-9764-70a22312fcc0/download
https://doi.org/10.26190/unsworks/30663

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

Authors: Rico, Julian Carvajal Alaeddini, Adel Faruqui, Syed Hasib Akhter et al.

Index Terms: Computer Science - Machine Learning, text

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