Výsledky vyhledávání - Constrained Graph Variational Autoencoder

  1. 1

    Conditional Constrained Graph Variational Autoencoders for Molecule Design Autor Rigoni, Davide, Navarin, Nicolo, Sperduti, Alessandro

    Vydáno: IEEE 01.12.2020
    “… We present Conditional Constrained Graph Variational Autoencoder (CCGVAE), a model that implements this key-idea in a state-of-the-art model, and shows improved results…”
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  2. 2

    Genetic Constrained Graph Variational Autoencoder for COVID-19 Drug Discovery Autor Cheng, Tianyue, Fan, Tianchi, Landi, Wang

    ISSN: 2331-8422
    Vydáno: Ithaca Cornell University Library, arXiv.org 23.04.2021
    Vydáno v arXiv.org (23.04.2021)
    “… (commonly known as SARS-CoV-2). We proposed a new model called Genetic Constrained Graph Variational Autoencoder (GCGVAE…”
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  3. 3

    Constrained Graph Variational Autoencoders for Molecule Design Autor Liu, Qi, Allamanis, Miltiadis, Brockschmidt, Marc, Gaunt, Alexander L

    ISSN: 2331-8422
    Vydáno: Ithaca Cornell University Library, arXiv.org 07.03.2019
    Vydáno v arXiv.org (07.03.2019)
    “… We propose a variational autoencoder model in which both encoder and decoder are graph-structured…”
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  4. 4

    Conditional Constrained Graph Variational Autoencoders for Molecule Design Autor Rigoni, Davide, Navarin, Nicolò, Sperduti, Alessandro

    ISSN: 2331-8422
    Vydáno: Ithaca Cornell University Library, arXiv.org 01.09.2020
    Vydáno v arXiv.org (01.09.2020)
    “… We present Conditional Constrained Graph Variational Autoencoder (CCGVAE), a model that implements this key-idea in a state-of-the-art model, and shows improved results…”
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  5. 5

    Physics-Constrained Predictive Molecular Latent Space Discovery with Graph Scattering Variational Autoencoder Autor Shervani-Tabar, Navid, Zabaras, Nicholas

    ISSN: 2331-8422
    Vydáno: Ithaca Cornell University Library, arXiv.org 11.02.2021
    Vydáno v arXiv.org (11.02.2021)
    “… In this work, we assess the predictive capabilities of a molecular generative model developed based on variational inference and graph theory in the small data regime…”
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  7. 7

    Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders Autor Ma, Tengfei, Chen, Jie, Cao, Xiao

    ISSN: 2331-8422
    Vydáno: Ithaca Cornell University Library, arXiv.org 19.09.2018
    Vydáno v arXiv.org (19.09.2018)
    “… These constraints are not easy to be incorporated into a generative model. In this work, we propose a regularization framework for variational autoencoders as a step…”
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  9. 9

    Geometry-Based Molecular Generation With Deep Constrained Variational Autoencoder Autor Li, Chunyan, Yao, Junfeng, Wei, Wei, Niu, Zhangming, Zeng, Xiangxiang, Li, Jin, Wang, Jianmin

    ISSN: 2162-237X, 2162-2388, 2162-2388
    Vydáno: United States IEEE 01.04.2024
    “… We proposed GEOM-CVAE, a constrained variational autoencoder based on geometric representation for molecular generation with specific properties, which is protein-context-dependent…”
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  10. 10

    OpenWGL: open-world graph learning for unseen class node classification Autor Wu, Man, Pan, Shirui, Zhu, Xingquan

    ISSN: 0219-1377, 0219-3116
    Vydáno: London Springer London 01.09.2021
    Vydáno v Knowledge and information systems (01.09.2021)
    “…Graph learning, such as node classification, is typically carried out in a closed-world setting…”
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  11. 11

    Predicting Protein-Protein Interactions Using Sequence and Network Information via Variational Graph Autoencoder Autor Luo, Xin, Wang, Liwei, Hu, Pengwei, Hu, Lun

    ISSN: 1545-5963, 1557-9964, 1557-9964
    Vydáno: United States IEEE 01.09.2023
    “… To overcome this problem, a novel PPI prediction algorithm, namely PASNVGA, is proposed in this work by combining the sequence and network information of proteins via variational graph autoencoder…”
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    Learning Graph Variational Autoencoders with Constraints and Structured Priors for Conditional Indoor 3D Scene Generation Autor Chattopadhyay, Aditya, Zhang, Xi, Wipf, David Paul, Arora, Himanshu, Vidal, Rene

    ISSN: 2642-9381
    Vydáno: IEEE 01.01.2023
    “…We present a graph variational autoencoder with a structured prior for generating the layout of indoor 3D scenes…”
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  13. 13

    Self-Organizing Maps-Assisted Variational Autoencoder for Unsupervised Network Anomaly Detection Autor Huang, Hailong, Yang, Jiahong, Zeng, Hang, Wang, Yaqin, Xiao, Liuming

    ISSN: 2073-8994, 2073-8994
    Vydáno: Basel MDPI AG 01.04.2025
    Vydáno v Symmetry (Basel) (01.04.2025)
    “… To overcome these limitations, this study proposes a self-organizing maps-assisted variational autoencoder (SOVAE) framework…”
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    Knowledge-embedding deep interpretable graph model for wear prediction: Application in pantograph-catenary systems Autor Mo, Yutao, Peng, Yizhen, Wu, Jing, Fan, Kangbo

    ISSN: 0951-8320
    Vydáno: Elsevier Ltd 01.09.2025
    “… on material parameters, environmental factors, and wear mechanisms are limited in accuracy. Purely data-driven approaches, on the other hand, are constrained…”
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    OpenWGL: Open-World Graph Learning Autor Wu, Man, Pan, Shirui, Zhu, Xingquan

    ISSN: 2374-8486
    Vydáno: IEEE 01.11.2020
    “…In traditional graph learning tasks, such as node classification, learning is carried out in a closed-world setting where the number of classes and their training samples are provided to help train…”
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  16. 16

    Vehicular Social Dynamic Anomaly Detection With Recurrent Multi-Mask Aggregator Enabled VAE Autor Hu, Zehao, He, Yuwei, Shen, Yuqi, Jo, Minho, Collotta, Mario, Shen, Guojiang, Kong, Xiangjie

    ISSN: 1524-9050, 1558-0016
    Vydáno: IEEE 01.12.2024
    “… However, Graph Attention Networks (GATs) are constrained by the univariate nature of attention heads and coefficients, thus lacking flexibility…”
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    TV-CCANM: a transformer variational inference in confounding cascade additive noise model for causal effect estimation Autor Ahmad, Sohail, Wang, Hong

    ISSN: 0094-9655, 1563-5163
    Vydáno: Taylor & Francis 22.09.2025
    “… While the Confounding Cascade Nonlinear Additive Noise Model (CCANM) coupled with variational autoencoders (VAEs…”
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    A Generative Framework for Predicting Antiferromagnets Autor Gong, Jianhu, Zhang, Zhengming, Fan, Zhenyu, Fu, Hanghang, Wang, Hongchang, Wang, Dunhui

    ISSN: 2198-3844, 2198-3844
    Vydáno: Germany 26.09.2025
    Vydáno v Advanced science (26.09.2025)
    “… Herein, an AFM design framework integrating a crystal diffusion variational autoencoder is presented with data augmentation (CDVAE‐DA…”
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    Unified Embeddings of Structural and Functional Connectome via a Function-Constrained Structural Graph Variational Auto-Encoder Autor Amodeo, Carlo, tel, Igor, Ajilore, Olusola, Zhan, Liang, Leow, Alex, Tulabandhula, Theja

    ISSN: 2331-8422
    Vydáno: Ithaca Cornell University Library, arXiv.org 05.07.2022
    Vydáno v arXiv.org (05.07.2022)
    “… leveraged to improve our understanding of the brain. To this end, we propose a function-constrained structural graph variational autoencoder (FCS-GVAE…”
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    Structured Graph Variational Autoencoders for Indoor Furniture layout Generation Autor Chattopadhyay, Aditya, Zhang, Xi, Wipf, David Paul, Arora, Himanshu, Vidal, Rene

    ISSN: 2331-8422
    Vydáno: Ithaca Cornell University Library, arXiv.org 22.07.2022
    Vydáno v arXiv.org (22.07.2022)
    “…We present a structured graph variational autoencoder for generating the layout of indoor 3D scenes…”
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    Paper