15 citations · 15 across the 4 of their papers we have counts for
4 papers
Multi-Agent Reinforcement Learning for Fast-Timescale Demand Response of Residential Loads
Vincent Mai, Philippe Maisonneuve, Tianyu Zhang +3
To integrate high amounts of renewable energy resources, electrical power grids must be able to cope with high amplitude, fast timescale variations in power generation. Frequency r…
Sample Efficient Deep Reinforcement Learning via Uncertainty Estimation
Vincent Mai, Kaustubh Mani, Liam Paull
In model-free deep reinforcement learning (RL) algorithms, using noisy value estimates to supervise policy evaluation and optimization is detrimental to the sample efficiency. As t…
Batch Inverse-Variance Weighting: Deep Heteroscedastic Regression
Vincent Mai, Waleed Khamies, Liam Paull
Heteroscedastic regression is the task of supervised learning where each label is subject to noise from a different distribution. This noise can be caused by the labelling process,…
Deep Active Localization
Sai Krishna, Keehong Seo, Dhaivat Bhatt +3
Active localization is the problem of generating robot actions that allow it to maximally disambiguate its pose within a reference map. Traditional approaches to this use an inform…