MATLAB and Simulink Seminars

MATLAB with PyTorch and TensorFlow


MATLAB® and Simulink® integrate with the deep learning frameworks PyTorch® and TensorFlow™, enabling engineers to use PyTorch and TensorFlow models in their tasks. This task can be to implement the complete AI workflow for their application or use AI to enhance existing system design workflows. For example, for models created in PyTorch or TensorFlow, you can use domain-specific data preprocessing, explain network decisions, and verify network robustness, simulate networks within a larger system, compress networks, and automatically generate code.

Explore the options and benefits, along with examples, of the three ways to integrate PyTorch and TensorFlow with MATLAB, along with various interoperability pathways available.


  • Model conversion between MATLAB, PyTorch, and TensorFlow
  • Co-execution of PyTorch and TensorFlow models in MATLAB
  • Co-execution of PyTorch and TensorFlow models in Simulink

This event is part of a series of related topics. View the full list of events in this series.

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