Search Results for author:
Found 5 papers, 3 papers with code
Spatiotemporally Constrained Action Space Attacks on Deep Reinforcement Learning Agents
In this work, we first frame the problem as an optimization problem of minimizing the cumulative reward of an RL agent with decoupled constraints as the budget of attack.
Multi-level 3D CNN for Learning Multi-scale Spatial Features
The multi-level voxel representation consists of a coarse voxel grid that contains volumetric information of the 3D object.
Learning and Visualizing Localized Geometric Features Using 3D-CNN: An Application to Manufacturability Analysis of Drilled Holes
3D Convolutional Neural Networks (3D-CNN) have been used for object recognition based on the voxelized shape of an object.
A Machine-Learning Framework for Design for Manufacturability
this is a duplicate submission(original is arXiv:1612. 02141).
Learning Localized Geometric Features Using 3D-CNN: An Application to Manufacturability Analysis of Drilled Holes
3D convolutional neural networks (3D-CNN) have been used for object recognition based on the voxelized shape of an object.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
