Search Results for author:
Found 7 papers, 4 papers with code
PointCutMix: Regularization Strategy for Point Cloud Classification
As 3D point cloud analysis has received increasing attention, the insufficient scale of point cloud datasets and the weak generalization ability of networks become prominent.
Ranked #3 on
3D Point Cloud Classification
on ModelNet40-C
3D Adversarial Attacks Beyond Point Cloud
In order to take advantage of the most effective gradient-based attack, a differentiable sample module that back-propagate the gradient of point cloud to mesh is introduced.
The art of defense: letting networks fool the attacker
To this end, in this paper, we propose a novel adversarial defense for 3D point cloud classifier that makes full use of the nature of the DNNs.
Boosting 3D Adversarial Attacks with Attacking On Frequency
Deep neural networks (DNNs) have been shown to be vulnerable to adversarial attacks.
Online Newton Step Algorithm with Estimated Gradient
In particular, we extend the ONS algorithm with the trick of expected gradient and develop a novel second-order online learning algorithm, i. e., Online Newton Step with Expected Gradient (ONSEG).
NeuReduce: Reducing Mixed Boolean-Arithmetic Expressions by Recurrent Neural Network
Mixed Boolean-Arithmetic (MBA) expressions involve both arithmetic calculation (e. g., plus, minus, multiply) and bitwise computation (e. g., and, or, negate, xor).
GraphMR: Graph Neural Network for Mathematical Reasoning
Mathematical reasoning aims to infer satisfiable solutions based on the given mathematics questions.
