677 citations · 915 across the 10 of their papers we have counts for
3 papers · 1 filter
Deep Graph Infomax
Petar Veličković, William Fedus, William L. Hamilton +3
We present Deep Graph Infomax (DGI), a general approach for learning node representations within graph-structured data in an unsupervised manner. DGI relies on maximizing mutual in…
Learning deep representations by mutual information estimation and maximization
R Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon +4
In this work, we perform unsupervised learning of representations by maximizing mutual information between an input and the output of a deep neural network encoder. Importantly, we…
On-line Adaptative Curriculum Learning for GANs
Thang Doan, Joao Monteiro, Isabela Albuquerque +4
Generative Adversarial Networks (GANs) can successfully approximate a probability distribution and produce realistic samples. However, open questions such as sufficient convergence…