Search Results for author:
Found 6 papers, 4 papers with code
Fast Point Cloud to Mesh Reconstruction for Deformable Object Tracking
For a robotic hand to control soft objects, it has to acquire online state feedback of the deforming object.
Real Robot Challenge 2022: Learning Dexterous Manipulation from Offline Data in the Real World
For this reason, a large part of the reinforcement learning (RL) community uses simulators to develop and benchmark algorithms.
Learning to Fly -- a Gym Environment with PyBullet Physics for Reinforcement Learning of Multi-agent Quadcopter Control
Robotic simulators are crucial for academic research and education as well as the development of safety-critical applications.
DSNAS: Direct Neural Architecture Search without Parameter Retraining
We argue that given a computer vision task for which a NAS method is expected, this definition can reduce the vaguely-defined NAS evaluation to i) accuracy of this task and ii) the total computation consumed to finally obtain a model with satisfying accuracy.
Ranked #16 on
Neural Architecture Search
on NAS-Bench-201, ImageNet-16-120
(Accuracy (Val) metric)
An Adversarial Approach to Private Flocking in Mobile Robot Teams
We present a method that generates private flocking controllers that hide the identity of the leader robot.
SNAS: Stochastic Neural Architecture Search
In experiments on CIFAR-10, SNAS takes less epochs to find a cell architecture with state-of-the-art accuracy than non-differentiable evolution-based and reinforcement-learning-based NAS, which is also transferable to ImageNet.
Ranked #25 on
Neural Architecture Search
on NAS-Bench-201, CIFAR-10
