咨询与建议

限定检索结果

文献类型

  • 1 篇 会议

馆藏范围

  • 1 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 1 篇 理学
    • 1 篇 数学
    • 1 篇 化学
    • 1 篇 生物学
  • 1 篇 工学
    • 1 篇 化学工程与技术
    • 1 篇 生物工程

主题

  • 1 篇 genome

机构

  • 1 篇 brandeis univers...
  • 1 篇 department of st...
  • 1 篇 probabilistic pr...
  • 1 篇 probabilistic pr...

作者

  • 1 篇 al-sibahi ahmad ...
  • 1 篇 hamelryck thomas
  • 1 篇 moreta lys sanz
  • 1 篇 theobald douglas
  • 1 篇 rønning ola
  • 1 篇 hein jotun

语言

  • 1 篇 英文
检索条件"机构=Probabilistic Programming Group"
1 条 记 录,以下是1-10 订阅
ANCESTRAL PROTEIN SEQUENCE RECONSTRUCTION USING A TREE-STRUCTURED ORNSTEIN-UHLENBECK VARIATIONAL AUTOENCODER  10
ANCESTRAL PROTEIN SEQUENCE RECONSTRUCTION USING A TREE-STRUC...
收藏 引用
10th International Conference on Learning Representations, ICLR 2022
作者: Moreta, Lys Sanz Rønning, Ola Al-Sibahi, Ahmad Salim Hein, Jotun Theobald, Douglas Hamelryck, Thomas Probabilistic Programming Group PLTC Section University of Copenhagen Copenhagen Denmark Department of Statistics University of Oxford Oxford United Kingdom Brandeis University Biochemistry Department MA United States Probabilistic Programming Group SCARB PLTC Section Department of Biology Computer Science University of Copenhagen Copenhagen Denmark
We introduce a deep generative model for representation learning of biological sequences that, unlike existing models, explicitly represents the evolutionary process. The model makes use of a tree-structured Ornstein-... 详细信息
来源: 评论