65 citations · 146 across the 5 of their papers we have counts for
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cs.LG2019★ 9 cited
Uncertainty-aware Model-based Policy Optimization
Tung-Long Vuong, Kenneth Tran
Model-based reinforcement learning has the potential to be more sample efficient than model-free approaches. However, existing model-based methods are vulnerable to model bias, whi…
stat.ML2019★ 65 cited
Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting
Aditya Grover, Jiaming Song, Alekh Agarwal +4
A learned generative model often produces biased statistics relative to the underlying data distribution. A standard technique to correct this bias is importance sampling, where sa…