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 ...
The fundamental mathematicalion of a network as a weighted graph brings to bear the tools of graph theory--a highly developed subject of mathematical research. But more importantly, recently proposed geometric notions of curvature on very general metric measure spaces allow us to utilize a whole ...
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，...
Current studies have discussed the aforementioned context. First, most of the literature on the chip trade focuses on the deconstruction of policy strategies4,9or insights into implications in frictional environments4,10and seldom employs complex network theory to examine the changing patterns in the s...
(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...
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 ...
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 ...
We show that the counting class LWPP remains unchanged even if one allows a polynomial number of gap values rather than one. On the other hand, we show tha
Topological data analysis (TDA) has achieved great success in measuring and quantifying shape-related properties of diverse data types, and has made an impact in areas such as disease classification [1], human activity modeling [2], network analysis [3], and many more applications [4–7]. To...