Entity type prediction is an important problem in knowledge graph (KG) research. A new KG entity type prediction method, named CORE (COmplex space Regression and Embedding), is proposed in this work. The proposed CORE method leverages the expressive power of two complex space embedding models;...

The fundamental connection between stochastic differential equations (SDEs) and partial differential equations (PDEs) has found numerous applications in diverse fields. We explore a similar link between stochastic calculus and combinatorial PDEs on graphs with Hodge structure, by showing that...

We study the number of isolated nodes in a soft random geometric graph whose vertices constitute a Poisson process on the torus of length L (the line segment [0 ,L ] with periodic boundary conditions), and where an edge is present between two nodes with a probability which depends on the...

Over the recent years, the study of Sliding Visibility Graph (SVG) algorithm has attracted great interests. The SVG algorithm is an effective method for quickly mapping time series to complex networks. In this paper, we propose the Sliding Horizontal Visibility Graph (SHVG) algorithm, a...

The paper investigates whether one can learn about the degree of climate risk exposure of firms by extracting information about their fundamentals and network connections and applying innovative graph-based artificial intelligence (AI) methodologies. We tackle this problem by creating a...

While venture capital firms are increasingly relying on recommendation models in investment decisions, existing startup recommendation models fail to consider the uniqueness of venture capital context, including two-sided matching between investing and investee firms and a lack of information...

I explore the merits and limitations of Pearl’s directed acyclic graphs (DAG) approach for identification in applied economics. Researchers rely on causal inference frameworks to derive causal effects from observational data. Econometricians use either the potential outcomes (PO) or the...

Given an input graph Gin =(V,E_in), we consider the problem of designing a sparse subgraph G = (V, E) with E ⊆ E_in that supports a large matching after some nodes in V are randomly deleted. We study three families of sparse graph designs (namely, Clusters, Rings, and Erdős-Rényi graphs) and...