498 citations · 1.8k across the 31 of their papers we have counts for
4 papers · 1 filter
Deep Unsupervised Clustering with Gaussian Mixture Variational Autoencoders
Nat Dilokthanakul, Pedro A. M. Mediano, Marta Garnelo +4
We study a variant of the variational autoencoder model (VAE) with a Gaussian mixture as a prior distribution, with the goal of performing unsupervised clustering through deep gene…
Towards Deep Symbolic Reinforcement Learning
Marta Garnelo, Kai Arulkumaran, Murray Shanahan
Deep reinforcement learning (DRL) brings the power of deep neural networks to bear on the generic task of trial-and-error learning, and its effectiveness has been convincingly demo…
Integrated Information and Metastability in Systems of Coupled Oscillators
Pedro A. M. Mediano, Juan Carlos Farah, Murray Shanahan
It has been shown that sets of oscillators in a modular network can exhibit a rich variety of metastable chimera states, in which synchronisation and desynchronisation coexist. Ind…
Classifying Options for Deep Reinforcement Learning
Kai Arulkumaran, Nat Dilokthanakul, Murray Shanahan +1
In this paper we combine one method for hierarchical reinforcement learning - the options framework - with deep Q-networks (DQNs) through the use of different "option heads" on the…