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20172022
most citedGraph Convolutional Matrix Completion

1.1k citations · 1.2k across the 11 of their papers we have counts for

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cs.LG20221 cited

Binding Actions to Objects in World Models

Ondrej Biza, Robert Platt, Jan-Willem van de Meent +2

We study the problem of binding actions to objects in object-factored world models using action-attention mechanisms. We propose two attention mechanisms for binding actions to obj…

cs.LG20224 cited

Symmetry Group Equivariant Architectures for Physics

Alexander Bogatskiy, Sanmay Ganguly, Thomas Kipf +8

Physical theories grounded in mathematical symmetries are an essential component of our understanding of a wide range of properties of the universe. Similarly, in the domain of mac…

cs.LG2021

The Impact of Negative Sampling on Contrastive Structured World Models

Ondrej Biza, Elise van der Pol, Thomas Kipf

World models trained by contrastive learning are a compelling alternative to autoencoder-based world models, which learn by reconstructing pixel states. In this paper, we describe…

cs.LG2020

Object-Centric Learning with Slot Attention

Francesco Locatello, Dirk Weissenborn, Thomas Unterthiner +5

Learning object-centric representations of complex scenes is a promising step towards enabling efficient abstract reasoning from low-level perceptual features. Yet, most deep learn…

cs.LG202013 cited

Plannable Approximations to MDP Homomorphisms: Equivariance under Actions

Elise van der Pol, Thomas Kipf, Frans A. Oliehoek +1

This work exploits action equivariance for representation learning in reinforcement learning. Equivariance under actions states that transitions in the input space are mirrored by…

cs.LG201925 cited

Image-Conditioned Graph Generation for Road Network Extraction

Davide Belli, Thomas Kipf

Deep generative models for graphs have shown great promise in the area of drug design, but have so far found little application beyond generating graph-structured molecules. In thi…