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Volumn , Issue , 2018, Pages

Wasserstein auto-encoders

Author keywords

[No Author keywords available]

Indexed keywords

LEARNING SYSTEMS;

EID: 85083952476     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (664)

References (33)
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    • Cuturi, M.1
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    • Training generative neural networks via maximum mean discrepancy optimization
    • G. K. Dziugaite, D. M. Roy, and Z. Ghahramani. Training generative neural networks via maximum mean discrepancy optimization. In UAI, 2015.
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  • 17
    • 85083952489 scopus 로고    scopus 로고
    • Auto-encoding variational Bayes
    • D. P. Kingma and M. Welling. Auto-encoding variational Bayes. In ICLR, 2014.
    • (2014) ICLR
    • Kingma, D.P.1    Welling, M.2
  • 18
    • 0032203257 scopus 로고    scopus 로고
    • Gradient-based learning applied to document recognition
    • Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner. Gradient-based learning applied to document recognition. In Proceedings of the IEEE, volume 86(11), pp. 2278–2324, 1998.
    • (1998) Proceedings of the IEEE , vol.86 , Issue.11 , pp. 2278-2324
    • LeCun, Y.1    Bottou, L.2    Bengio, Y.3    Haffner, P.4
  • 20
    • 84970016114 scopus 로고    scopus 로고
    • Generative moment matching networks
    • Y. Li, K. Swersky, and R. Zemel. Generative moment matching networks. In ICML, 2015.
    • (2015) ICML
    • Li, Y.1    Swersky, K.2    Zemel, R.3
  • 26
    • 85018914753 scopus 로고    scopus 로고
    • F-GaN: Training generative neural samplers using variational divergence minimization
    • Sebastian Nowozin, Botond Cseke, and Ryota Tomioka. f-GAN: Training generative neural samplers using variational divergence minimization. In NIPS, 2016.
    • (2016) NIPS
    • Nowozin, S.1    Cseke, B.2    Tomioka, R.3
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    • Unsupervised representation learning with deep convolutional generative adversarial networks
    • A. Radford, L. Metz, and S. Chintala. Unsupervised representation learning with deep convolutional generative adversarial networks. In ICLR, 2016.
    • (2016) ICLR
    • Radford, A.1    Metz, L.2    Chintala, S.3
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    • On the high-dimensional power of a linear-time two sample test under mean-shift alternatives
    • R. Reddi, A. Ramdas, A. Singh, B. Poczos, and L. Wasserman. On the high-dimensional power of a linear-time two sample test under mean-shift alternatives. In AISTATS, 2015.
    • (2015) AISTATS
    • Reddi, R.1    Ramdas, A.2    Singh, A.3    Poczos, B.4    Wasserman, L.5
  • 32
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    • Energy-based generative adversarial network
    • J. Zhao, M. Mathieu, and Y. LeCun. Energy-based generative adversarial network. In ICLR, 2017a.
    • (2017) ICLR
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.