Výsledky vyhledávání - improved conditioning variational autoencoder

Conditioning of variational autoencoder by user traits for item recommendation

Autoři: Tachioka, Yuuki

Témata: recommendation model, user traits, OCEAN (BigFive) traits, conditional variational autoencoder

Investigation of F0 conditioning and Fully Convolutional Networks in Variational Autoencoder based Voice Conversion

Autoři: Huang, Wen-Chin Wu, Yi-Chiao Lo, Chen-Chou a další

Témata: Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Sound, text

URL: http://arxiv.org/abs/1905.00615

Synthetic data generation for the optimization of strains in metabolic engineering using latent space representations derived from a Conditional Variational Autoencoder

Autoři: Alwani, Neil (author)

Témata: Metabolic Flux Analysis, Variational Autoencoder (VAE), Probabilistic analysis, Principal Component Analysis (PCA), Combinatorial Optimization, bachelor thesis

URL: http://resolver.tudelft.nl/uuid:0f0fbe65-257d-491d-9fe5-5c1b3864dfd4

Hierarchical and Multi-Scale Variational Autoencoder for Diverse and Natural Non-Autoregressive Text-to-Speech

Autoři: Bae, Jae-Sung Yang, Jinhyeok Bak, Tae-Jun a další

Témata: Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Sound, text

URL: http://arxiv.org/abs/2204.04004

MCVAE: A New Multi-Conditional Approach for Scalable Emergency Ad Hoc Network Design and Node Localization Using Generative Variational Autoencoder.

Autoři: Jabbar, M. A. A. Abbas, A. R. Ghani, R. F.

Zdroj: International Journal of Engineering Transactions C: Aspects; Jun2026, Vol. 39 Issue 6, p1390-1401, 12p

Témata: AD hoc computer networks, EMERGENCY management, REAL-time computing, AUTOENCODERS, PROBABILISTIC generative models, WIRELESS communications, SCALABILITY

Variational Autoencoder-Regulated Data Augmentation for Precise Estimation of Organic Pollutants in Water with Deeplearning Neural Network.

Autoři: Ashiquzzaman, Akm Kim, Jinsul Kim, Chihoon

Zdroj: Applied Artificial Intelligence; Dec2025, Vol. 39 Issue 1, p1-12, 12p

Structural Dynamics Feature Learning Using a Supervised Variational Autoencoder.

Autoři: Bacsa, Kiran Liu, Wei Abdallah, Imad a další

Zdroj: Journal of Engineering Mechanics; Feb2025, Vol. 151 Issue 2, p1-14, 14p

Témata: STRUCTURAL health monitoring, WIND turbine blades, AUTOENCODERS, STRUCTURAL dynamics, SUPERVISED learning

Lightweight Text-to-Image Generation Model Based on Contrastive Language-Image Pre-Training Embeddings and Conditional Variational Autoencoders.

Autoři: Wang, Yubo Zhang, Gaofeng

Zdroj: Electronics (2079-9292); Jun2025, Vol. 14 Issue 11, p2185, 31p

Témata: AUTOENCODERS, SUPPLY & demand, GENERALIZATION

Improved Generation of Drawing Sequences Using Variational and Skip-Connected Deep Networks for a Drawing Support System.

Autoři: Nakamura, Atomu Matsumoto, Homari Chiba, Koharu a další

Zdroj: Future Internet; Sep2025, Vol. 17 Issue 9, p413, 19p

Témata: DATA augmentation, DEEP learning, LATENT variables, NEURAL computers, GENERATIVE artificial intelligence, DRAWING techniques

ProT-VAE: Protein Transformer Variational AutoEncoder for functional protein design.

Autoři: Sevgen, Emre Moller, Joshua Lange, Adrian a další

Zdroj: Proceedings of the National Academy of Sciences of the United States of America; 10/14/2025, Vol. 122 Issue 41, p1-10, 21p

Témata: PROTEIN engineering, SYNTHETIC proteins, TRANSFORMER models, ENZYME biotechnology, FUNCTIONAL assessment, LATENT variables, MACHINE learning, PROBABILISTIC generative models

ECG Sensor Design Assessment with Variational Autoencoder-Based Digital Watermarking.

Autoři: Hsu, Chih-Yu Chang, Chih-Yin Chen, Yin-Chi a další

Zdroj: Sensors (14248220); Apr2025, Vol. 25 Issue 7, p2321, 26p

Témata: DIGITAL technology, DIGITAL watermarking, COPYRIGHT, DATA security, DETECTOR circuits

Latent space conditioning for improved classification and anomaly detection

Autoři: Norlander, Erik Sopasakis, Alexandros

Témata: Computer Science - Machine Learning, Statistics - Machine Learning, text

URL: http://arxiv.org/abs/1911.10599

Landslide Susceptibility Assessment via Imbalanced Data Augmentation with Tabular Variational Autoencoder and Quality–Diversity Post-Selection.

Autoři: Xu, Zhengyang Wang, Shitai Yin, Min a další

Zdroj: Applied Sciences (2076-3417); Nov2025, Vol. 15 Issue 22, p11965, 25p

Témata: LANDSLIDES, DATA augmentation, BOOSTING algorithms, NATURAL disasters, RISK assessment

A mechanical fault diagnosis model with semi-supervised variational autoencoder based on long short-term memory network.

Autoři: Qu, Yuanyuan Li, Tao Fu, Shichen a další

Zdroj: Nonlinear Dynamics; Jan2025, Vol. 113 Issue 1, p459-478, 20p

PIGPVAE: physics-informed gaussian process variational autoencoders.

Autoři: Spitieris, Michail Ruocco, Massimiliano Murad, Abdulmajid a další

Zdroj: Applied Intelligence; Aug2025, Vol. 55 Issue 12, p1-16, 16p

基于情感引导-扩散模型的藏族音乐生成网络. (Chinese)

Alternate Title: Emotion-driven diffusion model for Tibetan music generation. (English)

Autoři: 宋子牛 彭春燕 王龙辉 a další

Zdroj: Application Research of Computers / Jisuanji Yingyong Yanjiu; Aug2025, Vol. 42 Issue 8, p2283-2289, 7p

Témata: EMOTIONAL intelligence, MUSICAL composition, ARTIFICIAL intelligence, PROBABILISTIC generative models, FEATURE extraction, AUTOENCODERS

Anomaly Detection for Charging Piles Based on Conditional Variational Autoencoder.

Autoři: Wang, Chuanjun Lu, Yinyu Wang, Mingxin a další

Zdroj: International Transactions on Electrical Energy Systems; 9/23/2025, Vol. 2025, p1-12, 12p

Témata: ELECTRIC vehicles, SUPERVISED learning, PROBABILISTIC generative models, OUTLIER detection, SIGNAL detection, DISTRIBUTION (Probability theory), INFRASTRUCTURE (Economics)

ERLD-HC: Entropy-Regularized Latent Diffusion for Harmony-Constrained Symbolic Music Generation.

Autoři: Li, Yang

Zdroj: Entropy; Sep2025, Vol. 27 Issue 9, p901, 21p

Témata: HARMONICS (Music theory), AUTOENCODERS, SONGWRITING, MIDI (Standard), DEEP learning, PROBABILISTIC generative models, MACHINE learning, MUSICAL notation

SUBSET CONDITIONING USING VARIATIONAL AUTOENCODER WITH A LEARNABLE TENSOR TRAIN INDUCED PRIOR

Improved Anomaly Detection through Conditional Latent Space VAE Ensembles

Autoři: Åström, Oskar Sopasakis, Alexandros

Témata: Computer Science - Machine Learning, Computer Science - Computer Vision and Pattern Recognition, Mathematics - Probability, text

URL: http://arxiv.org/abs/2410.12328