Search Results for author: Victor Garcia Satorras

Found 6 papers, 5 papers with code

E(n) Equivariant Normalizing Flows

no code implementations19 May 2021 Victor Garcia Satorras, Emiel Hoogeboom, Fabian B. Fuchs, Ingmar Posner, Max Welling

This paper introduces a generative model equivariant to Euclidean symmetries: E(n) Equivariant Normalizing Flows (E-NFs).

E(n) Equivariant Graph Neural Networks

2 code implementations19 Feb 2021 Victor Garcia Satorras, Emiel Hoogeboom, Max Welling

This paper introduces a new model to learn graph neural networks equivariant to rotations, translations, reflections and permutations called E(n)-Equivariant Graph Neural Networks (EGNNs).

Representation Learning

The Convolution Exponential and Generalized Sylvester Flows

1 code implementation NeurIPS 2020 Emiel Hoogeboom, Victor Garcia Satorras, Jakub M. Tomczak, Max Welling

Empirically, we show that the convolution exponential outperforms other linear transformations in generative flows on CIFAR10 and the graph convolution exponential improves the performance of graph normalizing flows.

Neural Enhanced Belief Propagation on Factor Graphs

1 code implementation4 Mar 2020 Victor Garcia Satorras, Max Welling

In this work we first extend graph neural networks to factor graphs (FG-GNN).

Few-Shot Learning with Graph Neural Networks

1 code implementation ICLR 2018 Victor Garcia Satorras, Joan Bruna Estrach

We propose to study the problem of few-shot learning with the prism of inference on a partially observed graphical model, constructed from a collection of input images whose label can be either observed or not.

Active Learning Few-Shot Learning

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