We present SHIFT3D, a differentiable pipeline for generating 3D shapes t...
We demonstrate the first large-scale application of model-based generati...
We study the robustness of reinforcement learning (RL) with adversariall...
Recent papers have demonstrated that ensemble stumps and trees could be
...
Deep Reinforcement Learning (DRL) is vulnerable to small adversarial
per...
It is known that deep neural networks (DNNs) could be vulnerable to
adve...
Training neural networks with verifiable robustness guarantees is
challe...
Graph neural networks (GNNs) which apply the deep neural networks to gra...
We study the robustness verification problem for tree-based models, incl...
Although adversarial examples and model robustness have been extensively...
The adversarial training procedure proposed by Madry et al. (2018) is on...
The prediction accuracy has been the long-lasting and sole standard for
...
Verifying the robustness property of a general Rectified Linear Unit (Re...
Modern neural image captioning systems typically adopt the encoder-decod...
In this paper, we propose a novel method to estimate and characterize sp...