71 citations · 291 across the 21 of their papers we have counts for
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cs.AI2017★ 25 cited
TreeQN and ATreeC: Differentiable Tree-Structured Models for Deep Reinforcement Learning
Gregory Farquhar, Tim Rocktäschel, Maximilian Igl +1
Combining deep model-free reinforcement learning with on-line planning is a promising approach to building on the successes of deep RL. On-line planning with look-ahead trees has p…
stat.ML2017★ 71 cited
Auto-Encoding Sequential Monte Carlo
Tuan Anh Le, Maximilian Igl, Tom Rainforth +2
We build on auto-encoding sequential Monte Carlo (AESMC): a method for model and proposal learning based on maximizing the lower bound to the log marginal likelihood in a broad fam…