Deep multi-modal learning for joint linear representation of nonlinear dynamical systems

HIGHLIGHTS

  • who: Shaodi Qian from the Mechanical and Industrial Engineering, Northeastern University have published the research work: Deep multi-modal learning for joint linear representation of nonlinear dynamical systems, in the Journal: Scientific Reports Scientific Reports
  • what: In the first case study, the authors aim to test the joint linear dynamics extracted from multiple modalities. The authors evaluate the reconstruction and prediction accuracy and assess the model performance while one or more modalities are missing.

SUMMARY

    The system is usually analyzed by observations xl from different sources, which can be represented by . . .

     

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