NSTL国家科技图书文献中心

1. Deep generative models in energy system applications: Review, challenges, and future directions NSTL国家科技图书文献中心

Zhang X. | Glaws A.... - 《Applied energy》 - 2025,380(Feb.15) - 1.1～1.35 - 共35页

摘要： generative models (DGMs) underpinning these cutting-edge | generative artificial intelligence (GAI). Beyond | applications in text, speech, image, and video creation, deep | © 2024 Elsevier LtdIn recent years, with the | advent of mature machine learning products like ChatGPT

关键词： Deep generative models | Energy systems | Generative artificial intelligence | Smart grid

2. Extending intraday solar forecast horizons with deep generative models NSTL国家科技图书文献中心

Carpentieri A. | Folini D.... - 《Applied energy》 - 2025,377(Jan.1 Pt.A) - 1.1～1.14 - 共14页

摘要： present SHADECast, a deep* generative diffusion model for* | generative approach leads to up to 60% performance | -the-art deterministic models, showcasing the | © 2024 The AuthorsSurface solar irradiance | (SSI) plays a crucial role in tackling climate change

关键词： Diffusion models | Ensemble forecasts | Generative deep learning | Renewable energy integration | Solar irradiance | Spatiotemporal forecasting

3. Deep Generative Models for Therapeutic Peptide Discovery: A Comprehensive Review NSTL国家科技图书文献中心

LESHAN LAI | YUANSHENG LIU ... - 《ACM computing surveys》 - 2025,57(6) - 155.1～155.29 - 共29页

摘要： generative models (DGMs), provide opportunities to | Deep learning tools, especially deep | accelerate and simplify the design of drugs. As drug | candidates, peptides are superior to other biomolecules | because they combine potency, selectivity, and low

关键词： Bioinformatics | deep generative model | deep learning | peptides design

4. Report on the AAPM grand challenge on deep generative modeling for learning medical image statistics NSTL国家科技图书文献中心

Rucha Deshpande | Varun A. Kelkar ... - 《Medical Physics》 - 2025,52(1) - 4～20 - 共17页

摘要： benchmarking deep* generative models for medical image* | AAPM Grand Challenge on Deep* Generative Modeling for* | to promote the development of deep generative | models for medical imaging and to emphasize the need | , whereas the joint runners‐up employed a generative

关键词： deep generative models | DGM evaluation | grand challenge

5. Artificial intelligence in peptide-based drug design NSTL国家科技图书文献中心

Zhai, Silong | Liu, Tiantao ... - 《Drug discovery today》 - 2025,30(2) - Article 104300～Article 104300 - 共11页

摘要：, we explore the advanced deep* generative models for* | Protein-protein interactions (PPIs) are | fundamental to a variety of biological processes, but | targeting them with small molecules is challenging because | of their large and complex interaction interfaces

关键词： peptide design | artificial intelligence | protein-peptide interactions | deep generative models | protein-protein interactions

6. LEO: Generative Latent Image Animator for Human Video Synthesis NSTL国家科技图书文献中心

Wang, Yaohui | Ma, Xin ... - 《International Journal of Computer Vision》 - 2025,133(3) - 1277～1289 - 共13页

摘要：Spatio-temporal coherency is a major challenge | in synthesizing high quality videos, particularly | in synthesizing human videos that contain rich | global and local deformations. To resolve this | challenge, previous approaches have resorted to different

关键词： Video generation | Diffusion models | Human analysis | Deep generative models

7. Enhancing participatory planning with ChatGPT-assisted planning support systems: a hypothetical case study in Seoul NSTL国家科技图书文献中心

Quan, Steven Jige | Lee, Seojung - 《International journal of urban sciences》 - 2025,29(1) - 89～122 - 共34页

摘要： as deep* generative methods, offer new opportunities* | deep generative tools that enable stakeholders to | . Emerging large language models* (LLMs) like ChatGPT, along* | Recent advancements in technology for planning | support have led to increased interest in participatory

关键词： Planning support systems | Participatory planning | Artificial intelligence | Large language models | ChatGPT | Deep generative models | PRACTITIONERS | FRAMEWORK | DESIGN | TOOL...

8. Augmenting a spine CT scans dataset using VAEs, GANs, and transfer learning for improved detection of vertebral compression fractures NSTL国家科技图书文献中心

El Kojok Z. | Al Khansa H.... - 《Computers in Biology and Medicine》 - 2025,184 - 109446～109446 - 共16页

摘要：, generative* models have been extensively explored as a* | Deep Convolutional Generative Adverserial Networks | © 2024 The AuthorsIn recent years, deep | generated data to evaluate the generative* capabilities of* | models. The VAE-GAN model demonstrated the highest

关键词： Deep learning | Generative Adversarial Networks (GANs) | Generative models | Variational Autoencoders (VAEs) | Vertebral Compression Fractures (VCF)

9. Query-Efficient Model Inversion Attacks: An Information Flow View NSTL国家科技图书文献中心

Yixiao Xu | Binxing Fang ... - 《IEEE transactions on information forensics and security》 - 2025,20 - 1023～1036 - 共14页

摘要： limitations, employing generative* models to constrain the* | and the generation capability of generative models | deep learning, the primary challenges associated with | of these generative-based solutions, recent | generative-based MIAs within this theoretical framework, we

关键词： Data models | Training data | Training | Analytical models | Deep learning | Data privacy | Optimization | Mutual information | Image reconstruction | Generative adversarial networks

10. Generative Adversarial Network Based Image-Scaling Attack and Defense Modeling NSTL国家科技图书文献中心

Junjian Li | Honglong Chen ... - 《IEEE Transactions on Emerging Topics in Computational Intelligence》 - 2025,9(1) - 861～873 - 共13页

摘要： sizes of deep* learning models. However, such kind of* | Deep learning has achieved remarkable | attack model based on generative* adversarial network* | performance in computer vision applications, and gradually | becomes one of the mainstream technologies. Image

摘要： generative models (DGMs) underpinning these cutting-edge | generative artificial intelligence (GAI). Beyond | applications in text, speech, image, and video creation, deep | © 2024 Elsevier LtdIn recent years, with the | advent of mature machine learning products like ChatGPT

关键词： Deep generative models | Energy systems | Generative artificial intelligence | Smart grid

摘要： present SHADECast, a deep* generative diffusion model for* | generative approach leads to up to 60% performance | -the-art deterministic models, showcasing the | © 2024 The AuthorsSurface solar irradiance | (SSI) plays a crucial role in tackling climate change

关键词： Diffusion models | Ensemble forecasts | Generative deep learning | Renewable energy integration | Solar irradiance | Spatiotemporal forecasting

摘要： generative models (DGMs), provide opportunities to | Deep learning tools, especially deep | accelerate and simplify the design of drugs. As drug | candidates, peptides are superior to other biomolecules | because they combine potency, selectivity, and low

关键词： Bioinformatics | deep generative model | deep learning | peptides design

摘要： benchmarking deep* generative models for medical image* | AAPM Grand Challenge on Deep* Generative Modeling for* | to promote the development of deep generative | models for medical imaging and to emphasize the need | , whereas the joint runners‐up employed a generative

关键词： deep generative models | DGM evaluation | grand challenge

摘要：, we explore the advanced deep* generative models for* | Protein-protein interactions (PPIs) are | fundamental to a variety of biological processes, but | targeting them with small molecules is challenging because | of their large and complex interaction interfaces

关键词： peptide design | artificial intelligence | protein-peptide interactions | deep generative models | protein-protein interactions

摘要：Spatio-temporal coherency is a major challenge | in synthesizing high quality videos, particularly | in synthesizing human videos that contain rich | global and local deformations. To resolve this | challenge, previous approaches have resorted to different

关键词： Video generation | Diffusion models | Human analysis | Deep generative models

摘要： as deep* generative methods, offer new opportunities* | deep generative tools that enable stakeholders to | . Emerging large language models* (LLMs) like ChatGPT, along* | Recent advancements in technology for planning | support have led to increased interest in participatory

关键词： Planning support systems | Participatory planning | Artificial intelligence | Large language models | ChatGPT | Deep generative models | PRACTITIONERS | FRAMEWORK | DESIGN | TOOL...

摘要：, generative* models have been extensively explored as a* | Deep Convolutional Generative Adverserial Networks | © 2024 The AuthorsIn recent years, deep | generated data to evaluate the generative* capabilities of* | models. The VAE-GAN model demonstrated the highest

关键词： Deep learning | Generative Adversarial Networks (GANs) | Generative models | Variational Autoencoders (VAEs) | Vertebral Compression Fractures (VCF)

摘要： limitations, employing generative* models to constrain the* | and the generation capability of generative models | deep learning, the primary challenges associated with | of these generative-based solutions, recent | generative-based MIAs within this theoretical framework, we

关键词： Data models | Training data | Training | Analytical models | Deep learning | Data privacy | Optimization | Mutual information | Image reconstruction | Generative adversarial networks

摘要： sizes of deep* learning models. However, such kind of* | Deep learning has achieved remarkable | attack model based on generative* adversarial network* | performance in computer vision applications, and gradually | becomes one of the mainstream technologies. Image

关键词： Generative adversarial networks | Generators | Computational modeling | Training | Optimization | Deep learning | Data models

4008-161-200 800-990-8900

国家科技图书文献中心

摘要： generative models (DGMs) underpinning these cutting-edge | generative artificial intelligence (GAI). Beyond | applications in text, speech, image, and video creation, deep | © 2024 Elsevier LtdIn recent years, with the | advent of mature machine learning products like ChatGPT

关键词： Deep generative models | Energy systems | Generative artificial intelligence | Smart grid

摘要： present SHADECast, a deep generative diffusion model for | generative approach leads to up to 60% performance | -the-art deterministic models, showcasing the | © 2024 The AuthorsSurface solar irradiance | (SSI) plays a crucial role in tackling climate change

关键词： Diffusion models | Ensemble forecasts | Generative deep learning | Renewable energy integration | Solar irradiance | Spatiotemporal forecasting

摘要： generative models (DGMs), provide opportunities to | Deep learning tools, especially deep | accelerate and simplify the design of drugs. As drug | candidates, peptides are superior to other biomolecules | because they combine potency, selectivity, and low

关键词： Bioinformatics | deep generative model | deep learning | peptides design

摘要： benchmarking deep generative models for medical image | AAPM Grand Challenge on Deep Generative Modeling for | to promote the development of deep generative | models for medical imaging and to emphasize the need | , whereas the joint runners‐up employed a generative

关键词： deep generative models | DGM evaluation | grand challenge

摘要：, we explore the advanced deep generative models for | Protein-protein interactions (PPIs) are | fundamental to a variety of biological processes, but | targeting them with small molecules is challenging because | of their large and complex interaction interfaces

关键词： peptide design | artificial intelligence | protein-peptide interactions | deep generative models | protein-protein interactions

摘要：Spatio-temporal coherency is a major challenge | in synthesizing high quality videos, particularly | in synthesizing human videos that contain rich | global and local deformations. To resolve this | challenge, previous approaches have resorted to different

关键词： Video generation | Diffusion models | Human analysis | Deep generative models

摘要： as deep generative methods, offer new opportunities | deep generative tools that enable stakeholders to | . Emerging large language models (LLMs) like ChatGPT, along | Recent advancements in technology for planning | support have led to increased interest in participatory

关键词： Planning support systems | Participatory planning | Artificial intelligence | Large language models | ChatGPT | Deep generative models | PRACTITIONERS | FRAMEWORK | DESIGN | TOOL...

摘要：, generative models have been extensively explored as a | Deep Convolutional Generative Adverserial Networks | © 2024 The AuthorsIn recent years, deep | generated data to evaluate the generative capabilities of | models. The VAE-GAN model demonstrated the highest

关键词： Deep learning | Generative Adversarial Networks (GANs) | Generative models | Variational Autoencoders (VAEs) | Vertebral Compression Fractures (VCF)

摘要： limitations, employing generative models to constrain the | and the generation capability of generative models | deep learning, the primary challenges associated with | of these generative-based solutions, recent | generative-based MIAs within this theoretical framework, we

关键词： Data models | Training data | Training | Analytical models | Deep learning | Data privacy | Optimization | Mutual information | Image reconstruction | Generative adversarial networks

摘要： sizes of deep learning models. However, such kind of | Deep learning has achieved remarkable | attack model based on generative adversarial network | performance in computer vision applications, and gradually | becomes one of the mainstream technologies. Image

关键词： Generative adversarial networks | Generators | Computational modeling | Training | Optimization | Deep learning | Data models

4008-161-200 800-990-8900

国家科技图书文献中心

摘要： present SHADECast, a deep* generative diffusion model for* | generative approach leads to up to 60% performance | -the-art deterministic models, showcasing the | © 2024 The AuthorsSurface solar irradiance | (SSI) plays a crucial role in tackling climate change

摘要： benchmarking deep* generative models for medical image* | AAPM Grand Challenge on Deep* Generative Modeling for* | to promote the development of deep generative | models for medical imaging and to emphasize the need | , whereas the joint runners‐up employed a generative

摘要：, we explore the advanced deep* generative models for* | Protein-protein interactions (PPIs) are | fundamental to a variety of biological processes, but | targeting them with small molecules is challenging because | of their large and complex interaction interfaces

摘要： as deep* generative methods, offer new opportunities* | deep generative tools that enable stakeholders to | . Emerging large language models* (LLMs) like ChatGPT, along* | Recent advancements in technology for planning | support have led to increased interest in participatory

摘要：, generative* models have been extensively explored as a* | Deep Convolutional Generative Adverserial Networks | © 2024 The AuthorsIn recent years, deep | generated data to evaluate the generative* capabilities of* | models. The VAE-GAN model demonstrated the highest

摘要： limitations, employing generative* models to constrain the* | and the generation capability of generative models | deep learning, the primary challenges associated with | of these generative-based solutions, recent | generative-based MIAs within this theoretical framework, we

摘要： sizes of deep* learning models. However, such kind of* | Deep learning has achieved remarkable | attack model based on generative* adversarial network* | performance in computer vision applications, and gradually | becomes one of the mainstream technologies. Image