Neural expectation maximization

Klaus Greff, Sjoerd Van Steenkiste, Jürgen Schmidhuber

Research output: Chapter in Book/Report/Conference proceedingConference contribution


We introduce a novel framework for clustering that combines generalized EM with neural networks and can be implemented as an end-to-end differentiable recurrent neural network. It learns its statistical model directly from the data and can represent complex non-linear dependencies between inputs. We apply our framework to a perceptual grouping task and empirically verify that it yields the intended behavior as a proof of concept.
Original languageEnglish (US)
Title of host publication5th International Conference on Learning Representations, ICLR 2017 - Workshop Track Proceedings
PublisherInternational Conference on Learning Representations, ICLR
StatePublished - Jan 1 2019
Externally publishedYes


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