Graph neural networks have pushed state-of-the-arts in graph classifications recently. Typically, these methods are studied within the context of supervised end-to-end training, which necessities copious task-specific labels. However, real-world circumstances, labeled data could be limited, and there a massive corpus unlabeled data, even from unknown classes as complementary. Towards this end, ...

Let G = (V,E) be the IFG and D be set of vertices, then D is said to be Intuitionistic point set dominating set of G if for every S⊆ VD there exists a node d ∈ D such that the Intuitionistic fuzzy sub graph < S∪{d} > induced by S∪{d} is a connected Intuitionistic fuzzy graph. In this paper we study some results on Intuitionistic Point set dominating set and its number of IFGs. Also we establish...

We consider the problem of denoising a noisily sampled submanifold M in R, where the submanifold M is a priori unknown and we are only given a noisy point sample. The presented denoising algorithm is based on a graph-based diffusion process of the point sample. We analyze this diffusion process using recent results about the convergence of graph Laplacians. In the experiments we show that our m...

In this paper, we outline a model of graph (or network) dynamics based on two ingredients. The first ingredient is a Markov chain on the space of possible graphs. The second ingredient is a semi-Markov counting process of renewal type. The model consists in subordinating the Markov chain to the semi-Markov counting process. In simple words, this means that the chain transitions occur at random ...

Semi-directed 2-circulant graph is a subgraph of an (undirected) 2-circulant graph in which the links of one type (i.e., short or long) are directed while the other links are undirected. The shortest paths in semi-directed circulant graphs are called the restricted shortest paths in 2-circulant graphs. In this paper we show that the problem of finding the restricted shortest paths is equivalent...

Spectral clustering consists of two distinct stages: (a) construct an affinity graph from the dataset and (b) cluster the data points through finding an optimal partition of the affinity graph. The focus of the paper is the first step. Existing spectral clustering algorithms adopt Gaussian function to define the affinity graph since it is easy to implement. However, Gaussian function is hard to...

In 2006, Espinola and Kirk made a useful contribution on combining fixed point theoryand graph theory. Recently, Reich and Zaslavski studied a new inexact iterative scheme for fixed points of contractive and nonexpansive multifunctions. In this paper, by using  the main idea of their work and the idea of combining fixed point theory on intuitionistic fuzzy metric spaces and graph theory, ...