Výsledky vyhledávání - Bayesian Supervised Variational Autoencoder*

Learning from small medical data—robust semi-supervised cancer prognosis classifier with Bayesian variational autoencoder Autor Hsu, Te-Cheng, Lin, Che

“… Results We propose a robust Semi-supervised Cancer prognosis classifier with bAyesian variational autoeNcoder (SCAN…”
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SMAS: Structural MRI-based AD Score using Bayesian supervised VAE Autor Nemali, A., Bernal, J., Yakupov, R., Singh, D., Dyrba, M., Incesoy, E.I., Mukherjee, S., Peters, O., Ersözlü, E., Hellmann-Regen, J., Preis, L., Priller, J., Spruth, E., Altenstein, S., Lohse, A., Schneider, A., Fliessbach, K., Kimmich, O., Wiltfang, J., Hansen, N., Schott, B., Rostamzadeh, A., Glanz, W., Butryn, M., Buerger, K., Janowitz, D., Ewers, M., Perneczky, R., Rauchmann, B., Teipel, S., Kilimann, I., Goerss, D., Laske, C., Sodenkamp, S., Spottke, A., Coenjaerts, M., Brosseron, F., Lüsebrink, F., Dechent, P., Scheffler, K., Hetzer, S., Kleineidam, L., Stark, M., Jessen, F., Duzel, E., Ziegler, G.

“…)-related morphometric patterns using a deep learning Bayesian-supervised Variational Autoencoder (Bayesian-SVAE…”
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R/C buildings’ seismic damage prediction based on semi-supervised automatic differentiation variational inference deep autoencoder Autor Demertzis, K, Kostinakis, K, Morfidis, K, Iliadis, L

“…Structural damage from earthquakes has been assessed using a variety of methodologies, both statistical and, more recently, utilizing Machine Learning (ML)…”
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Structural MRI‐Based AD Score using Bayesian VAEs Autor Nemali, Aditya, Moyano, Jose Bernal, Yakupov, Renat, Schütze, Hartmut, Spottke, Annika, Ramirez, Alfredo, Schneider, Anja, Metzger, Coraline D., Laske, Christoph, Bittner, Daniel, Heneka, Michael T., Peters, Oliver, Speck, Oliver, Glanz, Wenzel, Wagner, Michael, Jessen, Frank, Düzel, Emrah, Ziegler, Gabriel

“…). To address these issues, we here propose a Structural MRI‐Based AD Score (SMAS) using a Bayesian supervised Variational Autoencoder (Bayesian sVAE…”
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SMAS: Structural MRI-Based AD Score using Bayesian VAE Autor Nemali, Aditya, Bernal, Jose, Yakupov, Renat, Singh, Devesh, Dyrba, Martin, Incesoy, Enise, Mukherjee, Sach, Peters, Oliver, Hellmann, Julian, Ersoezlue, Ersin, Preis, Lukas, Priller, Josef, Spruth, Eike, Altenstein, Slawek, Lohse, Andrea, Schneider, Anja, Fliessbach, Klaus, Kimmich, Okka, Wiltfang, Jens, Hansen, Niels, Schott, Bjoernhendrik, Rostamzadeh, Ayda, Glanz, Wenzel, Butryn, Michaela, Buerger, Katharina, Janowitz, Daniel, Ewers, Michael, Perneczky, Robert, Rauchmann, Boris, Teipel, Stefan, Kilimann, Ingo, Goerss, Doreen, Laske, Christoph, Sodenkamp, Sebastian, Spottke, Annika, Coenjaerts, Marie, Brosseron, Frederic, Falk Luesebrink, Dechent, Peter, Scheffler, Klaus, Hetzer, Stefan, Kleineidam, Luca, Stark, Melina, Jessen, Frank, Duezel, Emrah, Ziegler, Gabriel

“…) related morphometric patterns using a deep learning Bayesian supervised Variational Autoencoder (Bayesian sVAE…”
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Combining deep generative and discriminative models for Bayesian semi-supervised learning Autor Gordon, Jonathan, Hernández-Lobato, José Miguel

“…•Modelling framwork that enables Bayesian semi-supervised learning.•Bayesian semi-supervised improves overall performance and uncertainty calibration…”
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An Overview of Variational Autoencoders for Source Separation, Finance, and Bio-Signal Applications Autor Singh, Aman, Ogunfunmi, Tokunbo

“… Variational Autoencoders (VAEs) can be regarded as enhanced Autoencoders where a Bayesian approach is used to learn the probability distribution of the input…”
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Statistical Speech Enhancement Based on Probabilistic Integration of Variational Autoencoder and Non-Negative Matrix Factorization Autor Bando, Yoshiaki, Mimura, Masato, Itoyama, Katsutoshi, Yoshii, Kazuyoshi, Kawahara, Tatsuya

“…This paper presents a statistical method of single-channel speech enhancement that uses a variational autoencoder (VAE…”
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Reverse Variational Autoencoder: A probabilistic inference framework for structural health monitoring and inverse analysis in engineering Autor Zhao, Hao-yang, Wang, Chen, Fan, Jian-sheng

“… This study proposes a Bayesian deep learning-based framework, termed Reverse Variational Auto-Encoder (RVAE…”
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Optimizing training trajectories in variational autoencoders via latent Bayesian optimization approach Autor Biswas, Arpan, Vasudevan, Rama, Ziatdinov, Maxim, Kalinin, Sergei V

“…Unsupervised and semi-supervised ML methods such as variational autoencoders (VAE) have become widely adopted across multiple areas of physics, chemistry…”
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Grade: Generative graph contrastive learning for multimodal recommendation Autor Ping, Yu-Chao, Wang, Shu-Qin, Yang, Zi-Yi, Dong, Yong-Quan, Hu, Meng-Xiang, Zhang, Pei-Lin

“…-modal through variational graph reconstruction, effectively aligning modal features to improve user and item representations…”
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A generative artificial intelligence approach for antibiotic optimization Autor Torres, Marcelo D T, Zeng, Yimeng, Wan, Fangping, Maus, Natalie, Gardner, Jacob, de la Fuente-Nunez, Cesar

“…) framework that integrates a transformer-based variational autoencoder with Bayesian optimization to design and optimize antimicrobial peptides…”
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Multimodal Weibull Variational Autoencoder for Jointly Modeling Image-Text Data Autor Wang, Chaojie, Chen, Bo, Xiao, Sucheng, Wang, Zhengjue, Zhang, Hao, Wang, Penghui, Han, Ning, Zhou, Mingyuan

“… To alleviate the time-consuming Gibbs sampler adopted by traditional topic models in the testing stage, we construct a Weibull-based variational inference network (encoder…”
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Novel Semi-Supervised Seasonal-Trend VTN for Multimode Process IoT Soft Sensing Autor He, Yan-Lin, Zhou, Yang-Xiao-Yu, Xu, Yuan, Zhu, Qun-Xiong, Li, Xingyuan

“… Built on a variational Bayesian framework, ST-VTN models the regression…”
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Physics-constrained deep learning for biophysical parameter retrieval from Sentinel-2 images: Inversion of the PROSAIL model Autor Zérah, Yoël, Valero, Silvia, Inglada, Jordi

“…In this era of global warming, the regular and accurate mapping of vegetation conditions is essential for monitoring ecosystems, climate sustainability and…”
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Nonparametric Bayesian transfer learning for robust cardiopulmonary diseases classification in X-ray images Autor Haftu, Kibrom, Assabie, Yaregal

“… The deep transfer learning component extracts domain-invariant discriminating features using an Indian buffet process-driven variational autoencoder…”
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Deep clustering analysis via variational autoencoder with Gamma mixture latent embeddings Autor Guo, Jiaxun, Fan, Wentao, Amayri, Manar, Bouguila, Nizar

“…This article proposes a novel deep clustering model based on the variational autoencoder (VAE…”
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M2D-VAE: Self-Supervised Probabilistic Temporal-Spatial Latent Representation Learning for Unsupervised Industrial Operational Applications Under Missing Value Interference Autor Dai, Qingyang, Zhao, Chunhui, Huang, Biao

“… First, a novel deep dynamic probabilistic latent variable model, named Markov dynamic variational autoencoder (MD-VAE…”
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Context-Aware Learning for Generative Models Autor Perdikis, Serafeim, Leeb, Robert, Chavarriaga, Ricardo, Millan, Jose del R.

“… Using finite mixture models (FMMs) as the prototypical Bayesian network, we show that maximum-likelihood estimation (MLE…”
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Semi-Supervised Multichannel Speech Enhancement With a Deep Speech Prior Autor Sekiguchi, Kouhei, Bando, Yoshiaki, Nugraha, Aditya Arie, Yoshii, Kazuyoshi, Kawahara, Tatsuya

“…This paper describes a semi-supervised multichannel speech enhancement method that uses clean speech data for prior training…”
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