Cite GotenNet

BibTeX

@inproceedings{aykent2025gotennet,
  author = {Aykent, Sarp and Xia, Tian},
  title = {{GotenNet: Rethinking Efficient 3D Equivariant Graph Neural Networks}},
  booktitle = {The Thirteenth International Conference on Learning Representations},
  year = {2025},
  url = {https://openreview.net/forum?id=5wxCQDtbMo}
}

Other styles

APA
Aykent, S., & Xia, T. (2025). GotenNet: Rethinking Efficient 3D Equivariant Graph Neural Networks. The Thirteenth International Conference on Learning Representations. https://openreview.net/forum?id=5wxCQDtbMo
Vancouver
Aykent S, Xia T. GotenNet: Rethinking Efficient 3D Equivariant Graph Neural Networks. In: The Thirteenth International Conference on Learning Representations [Internet]. 2025. Available from: https://openreview.net/forum?id=5wxCQDtbMo
Harvard
Aykent, S. and Xia, T. (2025) “GotenNet: Rethinking Efficient 3D Equivariant Graph Neural Networks,” The Thirteenth International Conference on Learning Representations. Available at: https://openreview.net/forum?id=5wxCQDtbMo.
MLA
Aykent, Sarp, and Tian Xia. “GotenNet: Rethinking Efficient 3D Equivariant Graph Neural Networks.” The Thirteenth International Conference on Learning Representations, 2025, https://openreview.net/forum?id=5wxCQDtbMo.

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More recent publications

All publications

  • SaVeNet: A Scalable Vector Network for Enhanced Molecular Representation Learning

    Sarp Aykent, Tian Xia

    NeurIPS ,Thirty-seventh Conference on Neural Information Processing Systems

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    Cite SaVeNet

    BibTeX

    @inproceedings{aykent2023savenet,
  author = {Aykent, Sarp and Xia, Tian},
  title = {{SaVeNet: A Scalable Vector Network for Enhanced Molecular Representation Learning}},
  booktitle = {Thirty-seventh Conference on Neural Information Processing Systems},
  year = {2023}
}

    Other styles

    APA
    Aykent, S., & Xia, T. (2023). SaVeNet: A Scalable Vector Network for Enhanced Molecular Representation Learning. Thirty-Seventh Conference on Neural Information Processing Systems.
    Vancouver
    Aykent S, Xia T. SaVeNet: A Scalable Vector Network for Enhanced Molecular Representation Learning. In: Thirty-seventh Conference on Neural Information Processing Systems. 2023.
    Harvard
    Aykent, S. and Xia, T. (2023) “SaVeNet: A Scalable Vector Network for Enhanced Molecular Representation Learning,” Thirty-seventh Conference on Neural Information Processing Systems.
    MLA
    Aykent, Sarp, and Tian Xia. “SaVeNet: A Scalable Vector Network for Enhanced Molecular Representation Learning.” Thirty-Seventh Conference on Neural Information Processing Systems, 2023.

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  • GBPNet: Universal Geometric Representation Learning on Protein Structures

    Sarp Aykent, Tian Xia

    KDD ,Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery & Data Mining

    PDF (opens in new tab) Code (opens in new tab)

    Cite GBPNet

    BibTeX

    @inproceedings{gbp2022,
  author = {Aykent, Sarp and Xia, Tian},
  title = {{GBPNet: Universal Geometric Representation Learning on Protein Structures}},
  booktitle = {Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery \& Data Mining},
  series = {KDD '22},
  year = {2022},
  publisher = {Association for Computing Machinery},
  address = {Washington, DC, USA},
  isbn = {978-1-4503-9385-0/22/08}
}

    Other styles

    APA
    Aykent, S., & Xia, T. (2022). GBPNet: Universal Geometric Representation Learning on Protein Structures. Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, KDD ’22.
    Vancouver
    Aykent S, Xia T. GBPNet: Universal Geometric Representation Learning on Protein Structures. In: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery & Data Mining. Washington, DC, USA: Association for Computing Machinery; 2022. (KDD ’22).
    Harvard
    Aykent, S. and Xia, T. (2022) “GBPNet: Universal Geometric Representation Learning on Protein Structures,” Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery & Data Mining. Washington, DC, USA: Association for Computing Machinery (KDD ’22).
    MLA
    Aykent, Sarp, and Tian Xia. “GBPNet: Universal Geometric Representation Learning on Protein Structures.” Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery & Data Mining [Washington, DC, USA], KDD ’22, 2022.

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