Focused crawls are collections of frequently-updated webcrawl data from narrow (as opposed to broad or wide) web crawls, often focused on a single domain or subdomain.
This was reported to me by @max-andr. Most of the differences are actually explicitly mentioned in comments in our implementation, but we should check again if we can match the reference implementation more closely and possible mention deviations in the docs, not just in comments.
Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models. Advbox give a command line tool to generate adversarial examples with Zero-Coding.
I think it is necessary to add an experiment that compare the test accuracy of the original text and the adversarial text examples in the target model to judge whether the adversarial text examples really reduce the accuracy.
Pre-trained model, code, and materials from the paper "Impact of Adversarial Examples on Deep Learning Models for Biomedical Image Segmentation" (MICCAI 2019).
This is the implementation of MalConv proposed in [Malware Detection by Eating a Whole EXE](https://arxiv.org/abs/1710.09435) and its adversarial sample crafting.
This was reported to me by @max-andr. Most of the differences are actually explicitly mentioned in comments in our implementation, but we should check again if we can match the reference implementation more closely and possible mention deviations in the docs, not just in comments.
@max-andr might create a PR to fix this