In this paper, we propose a perturbation framework to measure the robustness\nof graph properties. Although there are already perturbation methods proposed\nto tackle this problem, they are limited by the fact that the strength of the\nperturbation cannot be well controlled. We firstly provide a ...
Intriguing properties of neural networks 认为对抗样本或不够鲁棒是因为模型正则化没有做好，过于复杂，...
We study a graph-theoretic property known as robustness, which plays a key role in certain classes of dynamics on networks (such as resilient consensus, contagion and bootstrap percolation). This property is stronger than other graph properties such as connectivity and minimum degree in that one ...
经典论文Intriguing properties of neural networks认为对抗样本或不够鲁棒是因为模型正则化没有做好，过于...
are utilised to aggregate genes into gene sets that share similar biological or functional properties. the resultant gene sets are analysed as a whole to identify which of these properties are relevant to the phenotype of interest [ 3 ]. pa methods overcome the limitations of interpreting ...
of GraphConv. Then we define the graph residual block consisting of two GraphConv+BatchNorm+ReLU blocks with a short connection (He et al.2016), as shown in Fig.2. For the initial block of the embedding sub-network and extracting sub-network, the input feature is the 3D coordinates of ...
(PrE) cells pattern the inner cell mass of mouse blastocysts. Coupling cell fate and dynamics, PrE cells form apical polarity-dependent actin protrusions required for RAC1-dependent migration towards the surface of the fluid cavity, where PrE cells are trapped due to decreased tension. ...
which are true examples perturbed with small artificial noise to fake the classifiers. Since that finding was reported, many methods have been proposed to study attacks on neural network using adversarial examples and defences against such adversarial attacks. This chapter discusses the theory of advers...
In a very general conceptual ap- proach, robustness R can be expressed as R� 1 , (1 + S) (1) where S represents the variation of system properties with respect to the variation of a generic system variable. In this way, an extremely robust structure has R � 1, whereas the ...
Complex networks are ubiquitous: a cell, the human brain, a group of people and the Internet are all examples of interconnected many-body systems characterized by macroscopic properties that cannot be trivially deduced from those of their microscopic constituents. Such systems are exposed to both int...