6–11 Jun 2021
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America/Toronto timezone
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(I) Interpreting artificial neural networks in the context of theoretical physics.

8 Jun 2021, 11:30
30m
Underline Conference System

Underline Conference System

Invited Speaker / Conférencier(ère) invité(e) Symposia Day (DTP) - Quantum Machine Learning TS-2 Quantum Machine Learning (DTP) / Apprentissage automatique quantique (DPT)

Speaker

Sebastian Wetzel

Description

Since many concepts in theoretical physics are well known to scientists in the form of equations, it is possible to identify such concepts in non-conventional applications of neural networks to physics.
In this talk we examine what is learned by convolutional neural networks, autoencoders or siamese networks in various physical domains. We find that these networks intrinsically learn physical concepts like order parameters, energies, or other conserved quantities.

Primary author

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