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[R] Symmetry-Based Disentangled Representation Learning requires Interaction with Environments

NeurIPS2019 paper, looks interesting:

https://arxiv.org/abs/1904.00243

Symmetry-Based Disentangled Representation Learning cannot only be based on static observations: agents should interact with the environment to discover its symmetries.

I’m not familiar with this line of research, but it seems like this could have significant implications on how models are trained, as many current benchmark datasets are static. I’d be interested in hearing thoughts from those more familiar with the method.

submitted by /u/rtk25
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.