Search Results - Multi-Modal 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

MyeVAE: a multi-modal variational autoencoder for risk profiling of newly diagnosed multiple myeloma

Authors: Jia Geng Chang Jianbin Chen Guo-Liang Chew et al.

Source: BMC Artificial Intelligence. 1

Improving Normative Modeling for Multi-Modal Neuroimaging Data Using Mixture-of-Product-of-Experts Variational Autoencoders

Authors: Kumar, Sayantan Payne, Philip Sotiras, Aristeidis

Source: 2024 IEEE International Symposium on Biomedical Imaging (ISBI). :1-5

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

Access URL: https://pubmed.ncbi.nlm.nih.gov/39610661
http://arxiv.org/abs/2312.00992

M^2VAE: Multi-Modal Multi-View Variational Autoencoder for Cold-start Item Recommendation

Authors: He, Chuan Liu, Yongchao Li, Qiang et al.

Subject Terms: FOS: Computer and information sciences, Artificial Intelligence (cs.AI), Artificial Intelligence, Information Retrieval, Information Retrieval (cs.IR)

Access URL: http://arxiv.org/abs/2508.00452

Personalized design aesthetic preference modeling: a variational autoencoder and meta-learning approach for multi-modal feature representation and transfer optimization.

Authors: Chen C Gong Z

Source: Scientific reports [Sci Rep] 2025 Nov 24; Vol. 15 (1), pp. 41727. Date of Electronic Publication: 2025 Nov 24.

Publication Type: Journal Article

Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: PubMed not MEDLINE; MEDLINE

Dmvae: a dual-stream multi-modal variational autoencoder for multi-task fake news detection

Authors: Ying Guo Shuting Hu Yao Li et al.

Source: Pattern Analysis and Applications. 28

No Reference Quality Assessment Metric for Multi-spectral and Multi-Modal Image Fusion using Sparse Approximate Variational Autoencoder

Authors: Patil, Milind S. Mane, Pradip B.

Source: International Journal of Intelligent Systems and Applications in Engineering; Vol. 12 No. 17s (2024); 724-732

Subject Terms: Deep Neural Network (DNN), Quality Assessment Regression Model, Sparse Approximate Variational Autoencoder

File Description: application/pdf

Access URL: https://www.ijisae.org/index.php/IJISAE/article/view/4941

Jointly Trained Variational Autoencoder for Multi-Modal Sensor Fusion

Authors: Korthals, Timo Hesse, Marc Leitner, Jürgen et al.

Source: 2019 22th International Conference on Information Fusion (FUSION). :1-8

Subject Terms: Variational Autoencoder, 0209 industrial biotechnology, publication, VAE, 0202 electrical engineering, electronic engineering, information engineering, multi-modal, 02 engineering and technology, Multi-Modal Fusion, MMVAE, Deep Generative Model

File Description: application/pdf

Access URL: https://pub.uni-bielefeld.de/record/2937521

Combined Generation of Electrocardiogram and Cardiac Anatomy Models Using Multi-Modal Variational Autoencoders

Authors: Beetz, M Banerjee, A Sang, Y et al.

Source: 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://ora.ox.ac.uk/objects/uuid:6b39a62e-5448-4731-b9d4-06041b082ea4
https://doi.org/10.1109/isbi52829.2022.9761590

CAVACHON: a hierarchical variational autoencoder to integrate multi-modal single-cell data

Authors: Hsieh, Ping-Han Hsiao, Ru-Xiu Ferenc, Katalin et al.

Index Terms: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Quantitative Biology - Genomics, text

URL: http://arxiv.org/abs/2405.18655

Multi-modal Vehicle Trajectory Prediction via Attention-based Conditional Variational Autoencoder

Authors: Hao Xing Jianming Hu Zuo Zhang

Source: 2022 37th Youth Academic Annual Conference of Chinese Association of Automation (YAC). :1367-1373

Multi-modal data generation with a deep metric variational autoencoder

Authors: Sundgaard, Josefine Vilsbøll Hannemose, Morten Rieger Laugesen, Søren et al.

Source: Proceedings of the Northern Lights Deep Learning Workshop; Vol. 4 (2023): Proceedings of the Northern Lights Deep Learning Workshop 2023

Subject Terms: FOS: Computer and information sciences, wideband tympanometry, Computer Vision and Pattern Recognition (cs.CV), deep metric learning, Image and Video Processing (eess.IV), Computer Science - Computer Vision and Pattern Recognition, generative modelling, otitis media, 02 engineering and technology, Electrical Engineering and Systems Science - Image and Video Processing, 01 natural sciences, otoscopy, FOS: Electrical engineering, electronic engineering, information engineering, 0202 electrical engineering, electronic engineering, information engineering, variational autoencoder, 0105 earth and related environmental sciences

File Description: application/pdf

Access URL: http://arxiv.org/abs/2202.03434
https://septentrio.uit.no/index.php/nldl/article/view/6803

Anytime 3D Object Reconstruction Using Multi-Modal Variational Autoencoder

Authors: Hyeonwoo Yu Jean Oh

Source: IEEE Robotics and Automation Letters. 7:2162-2169

Subject Terms: FOS: Computer and information sciences, 0209 industrial biotechnology, Computer Vision and Pattern Recognition (cs.CV), Computer Science - Computer Vision and Pattern Recognition, 02 engineering and technology

Access URL: https://scholarworks.unist.ac.kr/bitstream/201301/57246/1/000748560800031.pdf
http://arxiv.org/abs/2101.10391

InVA: Integrative Variational Autoencoder for Harmonization of Multi-modal Neuroimaging Data

Authors: Lei, Bowen Guhaniyogi, Rajarshi Chandra, Krishnendu et al.

Index Terms: Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Neural and Evolutionary Computing, Statistics - Applications, Statistics - Machine Learning, text

URL: http://arxiv.org/abs/2402.02734

Multi-Modal Domain Adaptation Variational Autoencoder for EEG-Based Emotion Recognition

Authors: Yixin Wang Shuang Qiu Dan Li et al.

Source: IEEE/CAA Journal of Automatica Sinica. 9:1612-1626

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

A Markov Random Field Multi-Modal Variational AutoEncoder

Authors: Oubari, Fouad Baha, Mohamed El Meunier, Raphael et al.

Index Terms: Computer Science - Machine Learning, Statistics - Machine Learning, text

URL: http://arxiv.org/abs/2408.09576

Modality Completion via Gaussian Process Prior Variational Autoencoders for Multi-modal Glioma Segmentation

Authors: Hamghalam, Mohammad Frangi, Alejandro F. Lei, Baiying et al.

Contributors: Hamghalam, Mohammad Frangi, Alejandro F. Lei, Baiying et al.

Source: Lecture Notes in Computer Science ISBN: 9783030872335
Hamghalam, M, Frangi, A F, Lei, B & Simpson, A L 2021, Modality Completion via Gaussian Process Prior Variational Autoencoders for Multi-modal Glioma Segmentation . in M de Bruijne, P C Cattin, S Cotin, N Padoy, S Speidel, Y Zheng & C Essert (eds), Medical Image Computing and Computer Assisted Intervention – MICCAI 2021-24th International Conference, Proceedings . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12907 LNCS, Springer Nature, pp. 442-452, 24th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2021, Virtual, Online, 27/09/21 . https://doi.org/10.1007/978-3-030-87234-2_42

Subject Terms: FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Vision and Pattern Recognition (cs.CV), Image and Video Processing (eess.IV), Computer Science - Computer Vision and Pattern Recognition, Variational autoencoder, 02 engineering and technology, Electrical Engineering and Systems Science - Image and Video Processing, Machine Learning (cs.LG), 03 medical and health sciences, 0302 clinical medicine, Glioma segmentation, Missing modality, 0202 electrical engineering, electronic engineering, information engineering, FOS: Electrical engineering, electronic engineering, information engineering, Gaussian process, MRI

Access URL: http://arxiv.org/pdf/2107.03442
http://arxiv.org/abs/2107.03442
https://arxiv.org/abs/2107.03442
https://dblp.uni-trier.de/db/journals/corr/corr2107.html#abs-2107-03442
https://link.springer.com/chapter/10.1007/978-3-030-87234-2_42
https://arxiv.org/pdf/2107.03442

Time-Lag Aware Multi-Modal Variational Autoencoder Using Baseball Videos And Tweets For Prediction Of Important Scenes

Authors: Miki Haseyama Keisuke Maeda Takahiro Ogawa et al.

Source: 2021 IEEE International Conference on Image Processing (ICIP). :2678-2682

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: http://xplorestaging.ieee.org/ielx7/9506008/9506009/09506496.pdf?arnumber=9506496

Improving Normative Modeling for Multi-modal Neuroimaging Data using mixture-of-product-of-experts variational autoencoders

Authors: Kumar, Sayantan Payne, Philip Sotiras, Aristeidis

Index Terms: Computer Science - Machine Learning, text

URL: http://arxiv.org/abs/2312.00992

Multi-modal data generation with a deep metric variational autoencoder

Authors: Sundgaard, Josefine Vilsbøll Hannemose, Morten Rieger Laugesen, Søren et al.

Index Terms: Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, text

URL: http://arxiv.org/abs/2202.03434