Set Flow: A Permutation Invariant Normalizing Flow

Permutation invariant likelihoods and equivariant transformations

Original

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Order matters: Sequence to sequence for sets

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O. Vinyals, S. Bengio, and M. Kudlur · 2016

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Density estimation using Real NVP, 2017

Original

L. Dinh, J. Sohl-Dickstein, and S. Bengio · 2017

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Masked autoregressive flow for density estimation

G. Papamakarios, T. Pavlakou, and I. Murray · 2017

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Automatic differentiation in pytorch

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Deep Sets

M. Zaheer, S. Kottur, S. Ravanbakhsh, B. Poczos, R. R. Salakhutdinov, and A. J. Smola · 2017

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Glow: Generative flow with invertible 1 × 1 1\times 1 convolutions

D. P. Kingma and P. Dhariwal · 2018

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Bruno: A deep recurrent model for exchangeable data

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Transformation autoregressive networks

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Janossy pooling: Learning deep permutation-invariant functions for variable-size inputs

R. L. Murphy, B. Srinivasan, V. Rao, and B. Ribeiro · 2019

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Learning representations of sets through optimized permutations

Y. Zhang, J. Hare, and A. Prügel-Bennett · 2019

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