Torchdyn reference documentationΒΆ

(New release 1.0 is out!)

torchdyn is a Python library entirely dedicated to continuous, implicit neural architectures and the numerical methods that underpin them.

It features a self-contained numerical suite of differential equation and root solvers, including sensitivity methods (continuous backsolve or interpolated adjoints, reverse-mode AD). The library further contains a model zoo and an extensive set of tutorials for researchers and practitioners.

pip install torchdyn

GitHub link.


  • This library is developed and maintained by Michael Poli & Stefano Massaroli, with gracious contributions from the community.

Refer to the links below for a quickstart to core torchdyn features and a description of the library goals and design principles.

A set of extended tutorials, covering everything from models, benchmarks and numerics can be found here.

Getting Started

API documentation

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