Výsledky vyhľadávania - ML: Deep Generative Models & Autoencoder

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

Autori: Sevgen, Emre Moller, Joshua Lange, Adrian a ďalší

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

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

Interpretable generative machine learning model based in-situ process monitoring in robotic wire arc based directed energy deposition of aluminum alloys.

Autori: Kumar, Deepak Jha, Sunil

Zdroj: CIRP: Journal of Manufacturing Science & Technology. Dec2025, Vol. 63, p185-204. 20p.

Predmety: Acoustic emission, Fault diagnosis, Process control systems, Metallurgical analysis, Aluminum alloys, Robotic welding, Generative artificial intelligence

Bridging the gap between machine learning and psychometrics.

Autori: Templin, Jonathan

Zdroj: Behaviormetrika; Jul2025, Vol. 52 Issue 2, p217-219, 3p

Predmety: MACHINE learning, PSYCHOMETRICS, ARTIFICIAL neural networks, FACTOR analysis, ITEM response theory, PROBABILISTIC generative models, SAT (Educational test)

Deep Generative Models for the Discovery of Antiviral Peptides Targeting Dengue Virus: A Systematic Review.

Autori: Duy, Huynh Anh Srisongkram, Tarapong

Zdroj: International Journal of Molecular Sciences; Jul2025, Vol. 26 Issue 13, p6159, 25p

Predmety: DENGUE viruses, ANTIVIRAL agents, ARTIFICIAL intelligence, DRUG discovery, PROBABILISTIC generative models, PEPTIDE synthesis, TREATMENT effectiveness, VIRAL replication

Deep Generative Models for Materials Discovery and Machine Learning-Accelerated Innovation

Autori: Addis S. Fuhr Bobby G. Sumpter

Zdroj: Frontiers in Materials, Vol 9 (2022)

Predmety: Technology, machine learning, generative models, inverse design, 02 engineering and technology, generative adversarial networks, 0210 nano-technology, 01 natural sciences, materials discovery, variational autoencoders, 0104 chemical sciences

Prístupová URL adresa: https://doaj.org/article/e61de32b93654efb969a59a7f996ce24

Optimizing Industry 5.0 Machine Learning-Based Applications via Synthetic Data Generation

Autori: Colombi, Lorenzo Brina, Matteo Vespa, Michela a ďalší

Zdroj: 2024 IEEE 29th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD). :1-6

Predmety: Industry 5.0 Machine Learning Deep Generative Model Generative Adversarial Network Diffusion Model Variational Auto encoder, Machine Learning, Variational Autoencoder, Deep Generative Model, Diffusion Model, Generative Adversarial Network, Industry 5.0

Popis súboru: application/pdf

Prístupová URL adresa: https://ieeexplore.ieee.org/document/10942898
https://doi.org/10.1109/CAMAD62243.2024.10942898
https://hdl.handle.net/11583/3000680
https://hdl.handle.net/11392/2587991
https://doi.org/10.1109/camad62243.2024.10942898
https://hdl.handle.net/11585/1014122
https://doi.org/10.1109/camad62243.2024.10942898

Cross-modal deep generative models reveal the cortical representation of dancing.

Autori: Takagi, Yu Shimizu, Daichi Wakabayashi, Mina a ďalší

Zdroj: Nature Communications; 11/18/2025, Vol. 16 Issue 1, p1-12, 12p

Predmety: DANCE, FUNCTIONAL magnetic resonance imaging, COGNITION, PROBABILISTIC generative models, EXPERTISE, EMOTIONAL experience

Inverse design of catalytic active sites via interpretable topology-based deep generative models.

Autori: Wang, Bingxu Zheng, Shisheng Wu, Jie a ďalší

Zdroj: NPJ Computational Materials; 5/24/2025, Vol. 11 Issue 1, p1-12, 12p

Predmety: HIGH-entropy alloys, CATALYST structure, AUTOENCODERS, CATALYSTS

Causal Inference with Conditional Instruments Using Deep Generative Models

Autori: Cheng, Debo Xu, Ziqi Li, Jiuyong a ďalší

Zdroj: Proceedings of the AAAI Conference on Artificial Intelligence; Vol. 37 No. 6: AAAI-23 Technical Tracks 6; 7122-7130 ; 2374-3468 ; 2159-5399

Predmety: ML: Deep Generative Models & Autoencoders, ML: Causal Learning, RU: Causality

Popis súboru: application/pdf

Relation: https://ojs.aaai.org/index.php/AAAI/article/view/25869/25641; https://ojs.aaai.org/index.php/AAAI/article/view/25869

Dostupnosť: https://ojs.aaai.org/index.php/AAAI/article/view/25869
https://doi.org/10.1609/aaai.v37i6.25869

On Explicit Curvature Regularization in Deep Generative Models

Autori: Lee, Yonghyeon Park, Frank Chongwoo

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

URL: http://arxiv.org/abs/2309.10237

Selective Deep Autoencoder for Unsupervised Feature Selection

Autori: Hassanieh, Wael Chehade, Abdallah

Zdroj: Proceedings of the AAAI Conference on Artificial Intelligence; Vol. 38 No. 11: AAAI-24 Technical Tracks 11; 12322-12330 ; 2374-3468 ; 2159-5399

Predmety: ML: Dimensionality Reduction/Feature Selection, DMKM: Data Compression, ML: Applications, ML: Deep Generative Models & Autoencoders, ML: Deep Neural Architectures and Foundation Models

Popis súboru: application/pdf

Relation: https://ojs.aaai.org/index.php/AAAI/article/view/29123/30124; https://ojs.aaai.org/index.php/AAAI/article/view/29123/30125; https://ojs.aaai.org/index.php/AAAI/article/view/29123

Dostupnosť: https://ojs.aaai.org/index.php/AAAI/article/view/29123
https://doi.org/10.1609/aaai.v38i11.29123

Recall-Oriented Continual Learning with Generative Adversarial Meta-Model

Autori: Kang, Haneol Choi, Dong-Wan

Zdroj: Proceedings of the AAAI Conference on Artificial Intelligence; Vol. 38 No. 12: AAAI-24 Technical Tracks 12; 13040-13048 ; 2374-3468 ; 2159-5399

Predmety: ML: Life-Long and Continual Learning, ML: Deep Generative Models & Autoencoders, ML: Bio-inspired Learning, ML: Deep Learning Algorithms

Popis súboru: application/pdf

Relation: https://ojs.aaai.org/index.php/AAAI/article/view/29202/30269; https://ojs.aaai.org/index.php/AAAI/article/view/29202/30270; https://ojs.aaai.org/index.php/AAAI/article/view/29202

Dostupnosť: https://ojs.aaai.org/index.php/AAAI/article/view/29202
https://doi.org/10.1609/aaai.v38i12.29202

Generative AI for cyber threat intelligence: applications, challenges, and analysis of real-world case studies.

Autori: Balasubramanian, Prasasthy Liyana, Sonali Sankaran, Hamsini a ďalší

Zdroj: Artificial Intelligence Review; Nov2025, Vol. 58 Issue 11, p1-134, 134p

Predmety: GENERATIVE artificial intelligence, CYBER intelligence (Computer security), COMPUTER network traffic, DIGITAL technology, CONTEXTUAL analysis, MALWARE, DATA privacy

Unified Framework for Diffusion Generative Models in SO(3): Applications in Computer Vision and Astrophysics

Autori: Jagvaral, Yesukhei Lanusse, Francois Mandelbaum, Rachel

Zdroj: Proceedings of the AAAI Conference on Artificial Intelligence; Vol. 38 No. 11: AAAI-24 Technical Tracks 11; 12754-12762 ; 2374-3468 ; 2159-5399

Predmety: ML: Learning with Manifolds, APP: Natural Sciences, APP: Other Applications, CV: Applications, CV: Vision for Robotics & Autonomous Driving, ML: Bayesian Learning, ML: Deep Generative Models & Autoencoders

Popis súboru: application/pdf

Relation: https://ojs.aaai.org/index.php/AAAI/article/view/29171/30215; https://ojs.aaai.org/index.php/AAAI/article/view/29171/30216; https://ojs.aaai.org/index.php/AAAI/article/view/29171

Dostupnosť: https://ojs.aaai.org/index.php/AAAI/article/view/29171
https://doi.org/10.1609/aaai.v38i11.29171

QCS-SGM+: Improved Quantized Compressed Sensing with Score-Based Generative Models

Autori: Meng, Xiangming Kabashima, Yoshiyuki

Zdroj: Proceedings of the AAAI Conference on Artificial Intelligence; Vol. 38 No. 13: AAAI-24 Technical Tracks 13; 14341-14349 ; 2374-3468 ; 2159-5399

Predmety: ML: Deep Generative Models & Autoencoders, ML: Bayesian Learning, ML: Probabilistic Circuits and Graphical Models

Popis súboru: application/pdf

Relation: https://ojs.aaai.org/index.php/AAAI/article/view/29347/30542; https://ojs.aaai.org/index.php/AAAI/article/view/29347/30543; https://ojs.aaai.org/index.php/AAAI/article/view/29347

Dostupnosť: https://ojs.aaai.org/index.php/AAAI/article/view/29347
https://doi.org/10.1609/aaai.v38i13.29347

Data Distribution Distilled Generative Model for Generalized Zero-Shot Recognition

Autori: Wang, Yijie Hong, Mingjian Huangfu, Luwen a ďalší

Zdroj: Proceedings of the AAAI Conference on Artificial Intelligence; Vol. 38 No. 6: AAAI-24 Technical Tracks 6; 5695-5703 ; 2374-3468 ; 2159-5399

Predmety: CV: Learning & Optimization for CV, CV: Representation Learning for Vision, ML: Deep Generative Models & Autoencoders

Popis súboru: application/pdf

Relation: https://ojs.aaai.org/index.php/AAAI/article/view/28381/28746; https://ojs.aaai.org/index.php/AAAI/article/view/28381/28747; https://ojs.aaai.org/index.php/AAAI/article/view/28381

Dostupnosť: https://ojs.aaai.org/index.php/AAAI/article/view/28381
https://doi.org/10.1609/aaai.v38i6.28381

Generative deep learning for predicting ultrahigh lattice thermal conductivity materials.

Autori: Guo, Liben Liu, Yuanbin Chen, Zekun a ďalší

Zdroj: NPJ Computational Materials; 4/11/2025, Vol. 11 Issue 1, p1-10, 10p

Predmety: MACHINE learning, THERMOPHYSICAL properties, THERMAL conductivity, CARBON-based materials, THERMAL properties

Continual Variational Autoencoder via Continual Generative Knowledge Distillation

Autori: Ye, Fei Bors, Adrian G.

Zdroj: Proceedings of the AAAI Conference on Artificial Intelligence; Vol. 37 No. 9: AAAI-23 Technical Tracks 9; 10918-10926 ; 2374-3468 ; 2159-5399

Predmety: ML: Deep Generative Models & Autoencoders, ML: Deep Learning Theory, ML: Ensemble Methods, ML: Lifelong and Continual Learning

Popis súboru: application/pdf

Relation: https://ojs.aaai.org/index.php/AAAI/article/view/26294/26066; https://ojs.aaai.org/index.php/AAAI/article/view/26294

Dostupnosť: https://ojs.aaai.org/index.php/AAAI/article/view/26294
https://doi.org/10.1609/aaai.v37i9.26294

Modeling protein–ligand interactions for drug discovery in the era of deep learning.

Autori: Wang, Yuzhe Li, Yibo Chen, Jiaxiao a ďalší

Zdroj: Chemical Society Reviews; 12/7/2025, Vol. 54 Issue 23, p11141-11183, 43p

Predmety: PROTEIN-ligand interactions, DRUG discovery, MOLECULAR dynamics, DRUG design, PREDICTION models, MOLECULAR docking, VIRTUAL high-throughput screening (Drug development), DEEP learning

Federated Generative Model on Multi-Source Heterogeneous Data in IoT

Autori: Xiong, Zuobin Li, Wei Cai, Zhipeng

Zdroj: Proceedings of the AAAI Conference on Artificial Intelligence; Vol. 37 No. 9: AAAI-23 Technical Tracks 9; 10537-10545 ; 2374-3468 ; 2159-5399

Predmety: ML: Deep Generative Models & Autoencoders, ML: Adversarial Learning & Robustness, ML: Distributed Machine Learning & Federated Learning

Popis súboru: application/pdf

Relation: https://ojs.aaai.org/index.php/AAAI/article/view/26252/26024; https://ojs.aaai.org/index.php/AAAI/article/view/26252

Dostupnosť: https://ojs.aaai.org/index.php/AAAI/article/view/26252
https://doi.org/10.1609/aaai.v37i9.26252