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MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation

MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation

27 May 2025
Felix Jahncke
Johannes Betz
ArXiv (abs)PDFHTML

Papers citing "MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation"

1 / 1 papers shown
Title
End-to-End Model-Free Reinforcement Learning for Urban Driving using
  Implicit Affordances
End-to-End Model-Free Reinforcement Learning for Urban Driving using Implicit Affordances
Marin Toromanoff
É. Wirbel
Fabien Moutarde
OffRL
157
209
0
25 Nov 2019
1