August 2022: We have released the slides used in the tutorial. Link:

July 2022: As part of the tutorial, we have released the source code for demo examples on how to use polynomial nets. Link:


Polynomial networks enable a new network design that treats a network as a high-degree polynomial expansion of the input. Recently, polynomial networks have demonstrated state-of-the-art performance in a range of tasks. Despite the fact that polynomial networks have appeared for several decades in machine learning and complex systems, they are not widely acknowledged for their role in modern deep learning.

In this tutorial we intend to bridge the gap and draw parallelisms between modern deep learning approaches and polynomial networks. To this end, we will share recent developments on the topic, as well as explain the required tools.

Schedule Detail

Tentative schedule.

  • 1.30 PM


  • 2.15 PM


  • 2.20 PM

    Higher-degree polynomials

  • 3.30 PM


  • 3.40 PM

    Recognition and generation with polynomial nets


CVPR 2022, New Orleans, Louisiana

Ernest N. Morial Convention Center, New Orleans


Following the guidelines of CVPR, this tutorial will take place on 20th June. You should register for the CVPR conference.
Please reach out at grigorios.chrysos [at] epfl [dot] ch.


organizer img

Markos Georgopoulos

Imperial College London

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Razvan Pascanu