47 citations · 124 across the 19 of their papers we have counts for
3 papers · 1 filter
MERACLE: Constructive layer-wise conversion of a Tensor Train into a MERA
Kim Batselier, Andrzej Cichocki, Ngai Wong
In this article two new algorithms are presented that convert a given data tensor train into either a Tucker decomposition with orthogonal matrix factors or a multi-scale entanglem…
Fastened CROWN: Tightened Neural Network Robustness Certificates
Zhaoyang Lyu, Ching-Yun Ko, Zhifeng Kong +3
The rapid growth of deep learning applications in real life is accompanied by severe safety concerns. To mitigate this uneasy phenomenon, much research has been done providing reli…
POPQORN: Quantifying Robustness of Recurrent Neural Networks
Ching-Yun Ko, Zhaoyang Lyu, Tsui-Wei Weng +3
The vulnerability to adversarial attacks has been a critical issue for deep neural networks. Addressing this issue requires a reliable way to evaluate the robustness of a network.…