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Academic Articles & Research Papers
Showing 20 of 29 academic articles
Maali Alabdulhafith, Abduljabbar S. Ba Mahel, Nagwan Abdel Samee, Noha F. Mahmoud et al. • Frontiers in Medicine
(2024)
Quality of life is greatly affected by chronic wounds. It requires more intensive care than acute wounds. Schedule follow-up appointments with their doctor to track healing. Good wound treatment promotes healing and fewer problems. Wound ca...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fmed.2024.1310137
Tianbao Song, Zongyi Huang, Xin Liu, Jingbo Sun • Entropy
(2025)
This paper introduces a novel variational autoencoder model termed DVAE to prevent posterior collapse in text modeling. DVAE employs a dual-path architecture within its decoder: path A and path B. Path A makes the direct input of text insta...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/e27040423
Chunmei Zhang, Aoran Zhang, Li Zhang, Yonghong Yu et al. • IEEE Access
(2024)
Learning high-quality representations of users, items, and tags from historical interactive data is crucial for personalized tag recommendation (PTR) systems. Currently, most PTR models are committed to learning representations from first-o...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2023.3347249
Andrii Tytarenko • Sistemnì Doslìdženâ ta Informacìjnì Tehnologìï
(2022)
In this paper, we derive a novel method as a generalization over LCEs such as E2C. The method develops the idea of learning a locally linear state space by adding a multi-step prediction, thus allowing for more explicit control over the cur...
DOAJ
Open Access (DOAJ)
DOI: 10.20535/SRIT.2308-8893.2022.3.09
Yashuai Wu, Ruiyang Yin, Wenjing Tian, Wanqiu Zhao et al. • Foods
(2026)
Umami taste in lager beer not only determined body fullness and the backbone of aftertaste, but also affected the controllability and interpretability of flavor expression across the entire brewing process. Based on stage-wise sampling, pep...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/foods15040641
Tongtong Huo, Wei Wu, Xiaoliang Chen, Mingdi Xue et al. • Intelligent Oncology
(2025)
Bone tumors (BTs)—including osteosarcoma, Ewing sarcoma, and chondrosarcoma—are rare but biologically complex malignancies characterized by pronounced heterogeneity in anatomical location, histological subtype, and molecular alterations. Re...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.intonc.2025.06.005
Zhiyuan Liu, Yankai Lin, Maosong Sun • Springer eBooks
(2020)
This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for NLP. It also benefit related domains such as machine learning, social network analysis, semantic Web, infor...
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DOI: https://doi.org/10.1007/978-981-15-5573-2
Chuxu Zhang, Dongjin Song, Chao Huang, Ananthram Swami et al. • ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
(2019)
Representation learning in heterogeneous graphs aims to pursue a meaningful vector representation for each node so as to facilitate downstream applications such as link prediction, personalized recommendation, node classification, etc. This...
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Open Access
DOI: https://doi.org/10.1145/3292500.3330961
Raban Iten, Tony Metger, Henrik Wilming, Lídia del Rio et al. • Physical Review Letters
(2020)
Despite the success of neural networks at solving concrete physics problems, their use as a general-purpose tool for scientific discovery is still in its infancy. Here, we approach this problem by modeling a neural network architecture afte...
OPENALEX
Open Access
DOI: https://doi.org/10.1103/physrevlett.124.010508
Yifan Feng, Haoxuan You, Zizhao Zhang, Rongrong Ji et al. • Proceedings of the AAAI Conference on Artificial Intelligence
(2019)
In this paper, we present a hypergraph neural networks (HGNN) framework for data representation learning, which can encode high-order data correlation in a hypergraph structure. Confronting the challenges of learning representation for comp...
OPENALEX
Open Access
DOI: https://doi.org/10.1609/aaai.v33i01.33013558
Zhiyuan Liu, Yankai Lin, Maosong Sun • Springer eBooks
(2023)
This open access book provides a comprehensive overview of the representation learning techniques for natural language processing....
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DOI: https://doi.org/10.1007/978-981-99-1600-9
Wazir Ali, Jay Kumar, Zenglin Xu, Rajesh Kumar et al. • Applied Sciences
(2021)
Named entity recognition (NER) is a fundamental task in many natural language processing (NLP) applications, such as text summarization and semantic information retrieval. Recently, deep neural networks (NNs) with the attention mechanism yi...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app11199038
Lingfei Wu, Yu Chen, Kai Shen, Xiaojie Guo et al. • Foundations and Trends® in Machine Learning
(2023)
Deep learning has become the dominant approach in addressing various tasks in Natural Language Processing (NLP). Although text inputs are typically represented as a sequence of tokens, there is a rich variety of NLP problems that can be bes...
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Open Access
DOI: https://doi.org/10.1561/2200000096
Hang Li • National Science Review
(2017)
Deep learning refers to machine learning technologies for learning and utilizing ‘deep’ artificial neural networks, such as deep neural networks (DNN), convolutional neural networks (CNN) and recurrent neural networks (RNN). Recently, deep ...
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DOI: https://doi.org/10.1093/nsr/nwx110
Chrisantus Eze, Christopher Crick • IEEE Access
(2025)
Robot learning of manipulation skills is hindered by the scarcity of diverse, unbiased datasets. While curated datasets can help, challenges remain regarding generalizability and real-world transfer. Meanwhile, large-scale ‘in-the-wi...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3624723
Congcong Zhang, Jin Tian, Lihua Gong, Yujin Zhang et al. • Applied Sciences
(2026)
Video prediction is a fundamental task in computer vision with broad applications in intelligent robotics, autonomous driving, and related fields. However, existing methods often struggle to simultaneously model long-term temporal dependenc...
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Open Access (DOAJ)
DOI: 10.3390/app16094423
Samyakh Tukra, Haozheng Xu, Chi Xu, Stamatia Giannarou • Healthcare Technology Letters
(2024)
Abstract Generalizable and accurate stereo depth estimation is vital for 3D reconstruction, especially in surgery. Supervised learning methods obtain best performance however, limited ground truth data for surgical scenes limits generalizab...
DOAJ
Open Access (DOAJ)
DOI: 10.1049/htl2.12067
Opeyemi Bamigbade, Mark Scanlon, John Sheppard • IEEE Access
(2025)
Embeddings remain the best way to represent image features, but do not always capture all latent information. This is still a problem in representation learning, and computer vision descriptors struggle with precision and accuracy. Improvin...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3564496
Qingyang Xiao, Kaiyuan Liu, Yuhui Hong, Haixu Tang • ACS in focus
(2024)
In recent years, breakthroughs in artificial intelligence (AI) have dramatically transformed many fields. Developments in neural networks primarily drive the advances. These powerful models have demonstrated unprecedented capabilities in le...
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DOI: https://doi.org/10.1021/acsinfocus.7e8012
Senzhang Wang, Jiannong Cao, Philip S. Yu • IEEE Transactions on Knowledge and Data Engineering
(2020)
With the fast development of various positioning techniques such as Global Position System (GPS), mobile devices and remote sensing, spatio-temporal data has become increasingly available nowadays. Mining valuable knowledge from spatio-temp...
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Open Access
DOI: https://doi.org/10.1109/tkde.2020.3025580