Combines offline behavioral cloning with online Real-Time Recurrent RL fine-tuning on LrcSSM models to adapt autonomous driving policies to distribution shifts, validated in simulation and on a real 1:10-scale robot with event camera.
Learning with chemical versus electrical synapses does it make a difference? In2024 IEEE Inter- national Conference on Robotics and Automation (ICRA), pp
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A framework based on linear dynamical systems unifies fixed-point iteration schemes such as Newton, Picard, and Jacobi as approximate linearizations of nonlinear recursions for parallelizing sequential models.
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Adaptive Control in Autonomous Driving via Real-Time Recurrent RL
Combines offline behavioral cloning with online Real-Time Recurrent RL fine-tuning on LrcSSM models to adapt autonomous driving policies to distribution shifts, validated in simulation and on a real 1:10-scale robot with event camera.
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A Unifying Framework for Parallelizing Sequential Models with Linear Dynamical Systems
A framework based on linear dynamical systems unifies fixed-point iteration schemes such as Newton, Picard, and Jacobi as approximate linearizations of nonlinear recursions for parallelizing sequential models.