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Sungjin Ahn

Rutgers, The State University

    • 396 Citations
    • 11 h-Index
    20052019
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    Research Output 2005 2019

    • 396 Citations
    • 11 h-Index
    • 13 Conference contribution
    • 3 Paper
    • 2 Conference article

    Hierarchical multiscale recurrent neural networks

    Ahn, S., Jan 1 2019.

    Research output: Contribution to conference › Paper

    Recurrent neural networks
    neural network
    handwriting
    evidence
    lack

    Bayesian model-agnostic meta-learning

    Ahn, S., Jan 1 2018, In : Advances in Neural Information Processing Systems. 2018-December, p. 7332-7342 11 p.

    Rutgers, The State University

    Research output: Contribution to journal › Conference article

    Reinforcement learning
    Image classification
    Experiments
    Uncertainty
    Problem-Based Learning

    Denoising criterion for variational auto-encoding framework

    Ahn, S., Jan 1 2017, p. 2059-2065. 7 p.

    Rutgers, The State University

    Research output: Contribution to conference › Paper

    4 Citations (Scopus)

    SENA: Preserving social structure for network embedding

    Ahn, S., Jul 4 2017, HT 2017 - Proceedings of the 28th ACM Conference on Hypertext and Social Media. Association for Computing Machinery, Inc, p. 235-244 10 p. (HT 2017 - Proceedings of the 28th ACM Conference on Hypertext and Social Media).

    Rutgers, The State University

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

    Electric network analysis

    Generating factoid questionswith recurrent neural networks: The 30M factoid question-answer corpus

    Ahn, S., Jan 1 2016, 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - Long Papers. Association for Computational Linguistics (ACL), p. 588-598 11 p. (54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - Long Papers; vol. 1).

    Rutgers, The State University

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

    neural network
    evaluation
    learning
    language
    Recurrent Neural Networks