11 citations · 13 across the 3 of their papers we have counts for
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cs.LG2021★ 11 cited
High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning
Antoine Grosnit, Rasul Tutunov, Alexandre Max Maraval +9
We introduce a method combining variational autoencoders (VAEs) and deep metric learning to perform Bayesian optimisation (BO) over high-dimensional and structured input spaces. By…
cs.LG2020★ 1 cited
Deep Reinforcement Learning with Linear Quadratic Regulator Regions
Gabriel I. Fernandez, Colin Togashi, Dennis W. Hong +1
Practitioners often rely on compute-intensive domain randomization to ensure reinforcement learning policies trained in simulation can robustly transfer to the real world. Due to u…