5 citations · 5 across the 2 of their papers we have counts for
2 papers
cs.RO2023
Learning to Explore Indoor Environments using Autonomous Micro Aerial Vehicles
Yuezhan Tao, Eran Iceland, Beiming Li +7
In this paper, we address the challenge of exploring unknown indoor aerial environments using autonomous aerial robots with Size Weight and Power (SWaP) constraints. The SWaP const…
cs.LG2012★ 5 cited
What Cannot be Learned with Bethe Approximations
Uri Heinemann, Amir Globerson
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its Be…