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Found 2 papers, 1 papers with code
A Unifying Variational Framework for Gaussian Process Motion Planning
To control how a robot moves, motion planning algorithms must compute paths in high-dimensional state spaces while accounting for physical constraints related to motors and joints, generating smooth and stable motions, avoiding obstacles, and preventing collisions.
Investigating the Edge of Stability Phenomenon in Reinforcement Learning
Recent progress has been made in understanding optimisation dynamics in neural networks trained with full-batch gradient descent with momentum with the uncovering of the edge of stability phenomenon in supervised learning.
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