Search Results - Constrained Graph Variational Autoencoder

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  1. 1

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

    Published: 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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    Conference Proceeding
  2. 2

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

    ISSN: 2331-8422
    Published: Ithaca Cornell University Library, arXiv.org 23.04.2021
    Published in 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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    Paper
  3. 3

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

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

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

    ISSN: 2331-8422
    Published: Ithaca Cornell University Library, arXiv.org 01.09.2020
    Published in 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…”
    Get full text
    Paper
  5. 5

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

    ISSN: 2331-8422
    Published: Ithaca Cornell University Library, arXiv.org 11.02.2021
    Published in 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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    Paper
  6. 6
  7. 7

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

    ISSN: 2331-8422
    Published: Ithaca Cornell University Library, arXiv.org 19.09.2018
    Published in 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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    Paper
  8. 8
  9. 9

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

    ISSN: 2162-237X, 2162-2388, 2162-2388
    Published: 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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    Journal Article
  10. 10

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

    ISSN: 0219-1377, 0219-3116
    Published: London Springer London 01.09.2021
    Published in 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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    Journal Article
  11. 11

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

    ISSN: 1545-5963, 1557-9964, 1557-9964
    Published: 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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    Journal Article
  12. 12

    Learning Graph Variational Autoencoders with Constraints and Structured Priors for Conditional Indoor 3D Scene Generation by Chattopadhyay, Aditya, Zhang, Xi, Wipf, David Paul, Arora, Himanshu, Vidal, Rene

    ISSN: 2642-9381
    Published: 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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    Conference Proceeding
  13. 13

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

    ISSN: 2073-8994, 2073-8994
    Published: Basel MDPI AG 01.04.2025
    Published in 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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    Journal Article
  14. 14

    Knowledge-embedding deep interpretable graph model for wear prediction: Application in pantograph-catenary systems by Mo, Yutao, Peng, Yizhen, Wu, Jing, Fan, Kangbo

    ISSN: 0951-8320
    Published: Elsevier Ltd 01.09.2025
    Published in Reliability engineering & system safety (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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    Journal Article
  15. 15

    OpenWGL: Open-World Graph Learning by Wu, Man, Pan, Shirui, Zhu, Xingquan

    ISSN: 2374-8486
    Published: 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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    Conference Proceeding
  16. 16

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

    ISSN: 1524-9050, 1558-0016
    Published: 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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    Journal Article
  17. 17

    TV-CCANM: a transformer variational inference in confounding cascade additive noise model for causal effect estimation by Ahmad, Sohail, Wang, Hong

    ISSN: 0094-9655, 1563-5163
    Published: Taylor & Francis 22.09.2025
    “… While the Confounding Cascade Nonlinear Additive Noise Model (CCANM) coupled with variational autoencoders (VAEs…”
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    Journal Article
  18. 18

    A Generative Framework for Predicting Antiferromagnets by Gong, Jianhu, Zhang, Zhengming, Fan, Zhenyu, Fu, Hanghang, Wang, Hongchang, Wang, Dunhui

    ISSN: 2198-3844, 2198-3844
    Published: Germany 26.09.2025
    Published in 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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    Journal Article
  19. 19

    Unified Embeddings of Structural and Functional Connectome via a Function-Constrained Structural Graph Variational Auto-Encoder by Amodeo, Carlo, tel, Igor, Ajilore, Olusola, Zhan, Liang, Leow, Alex, Tulabandhula, Theja

    ISSN: 2331-8422
    Published: Ithaca Cornell University Library, arXiv.org 05.07.2022
    Published in 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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    Paper
  20. 20

    Structured Graph Variational Autoencoders for Indoor Furniture layout Generation by Chattopadhyay, Aditya, Zhang, Xi, Wipf, David Paul, Arora, Himanshu, Vidal, Rene

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