1 code implementation • 17 Apr 2024 • James Harrison, John Willes, Jasper Snoek
We introduce a deterministic variational formulation for training Bayesian last layer neural networks.
1 code implementation • 5 Dec 2023 • Matthew Choi, Muhammad Adil Asif, John Willes, David Emerson
With the growth of large language models, now incorporating billions of parameters, the hardware prerequisites for their training and deployment have seen a corresponding increase.
no code implementations • 10 Aug 2023 • Marshall Wang, John Willes, Thomas Jiralerspong, Matin Moezzi
Reinforcement learning (RL) is a promising approach for optimizing HVAC control.
no code implementations • 17 Aug 2022 • John Willes, Cody Reading, Steven L. Waslander
We then perform a learned regression on each track/detection feature pair to estimate affinities, and use a robust two-stage data association and track management approach to produce the final tracks.
no code implementations • 29 Jul 2021 • John Willes, James Harrison, Ali Harakeh, Chelsea Finn, Marco Pavone, Steven Waslander
As autonomous decision-making agents move from narrow operating environments to unstructured worlds, learning systems must move from a closed-world formulation to an open-world and few-shot setting in which agents continuously learn new classes from small amounts of information.