4.6k citations · 9.5k across the 33 of their papers we have counts for
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cs.LG2016★ 13 cited
Improving Sampling from Generative Autoencoders with Markov Chains
Antonia Creswell, Kai Arulkumaran, Anil Anthony Bharath
We focus on generative autoencoders, such as variational or adversarial autoencoders, which jointly learn a generative model alongside an inference model. Generative autoencoders a…
cs.LG2016★ 19 cited
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…