
An Interpretable Graph Generative Model with Heterophily
Many models for graphs fall under the framework of edgeindependent dot ...
read it

Influenceguided Data Augmentation for Neural Tensor Completion
How can we predict missing values in multidimensional data (or tensors)...
read it

Optimal Space and Time for Streaming Pattern Matching
In this work, we study longest common substring, pattern matching, and w...
read it

Edge: Enriching Knowledge Graph Embeddings with External Text
Knowledge graphs suffer from sparsity which degrades the quality of repr...
read it

Insightcentric Visualization Recommendation
Visualization recommendation systems simplify exploratory data analysis ...
read it

Personalized Visualization Recommendation
Visualization recommendation work has focused solely on scoring visualiz...
read it

Fundamental Tradeoffs in Distributionally Adversarial Training
Adversarial training is among the most effective techniques to improve t...
read it

Heterogeneous Graphlets
In this paper, we introduce a generalization of graphlets to heterogeneo...
read it

Graph Deep Factors for Forecasting
Deep probabilistic forecasting techniques have recently been proposed fo...
read it

Graph Neural Networks with Heterophily
Graph Neural Networks (GNNs) have proven to be useful for many different...
read it

A Context Integrated Relational SpatioTemporal Model for Demand and Supply Forecasting
Traditional methods for demand forecasting only focus on modeling the te...
read it

MLbased Visualization Recommendation: Learning to Recommend Visualizations from Data
Visualization recommendation seeks to generate, score, and recommend to ...
read it

From Static to Dynamic Node Embeddings
We introduce a general framework for leveraging graph stream data for te...
read it

Structured Policy Iteration for Linear Quadratic Regulator
Linear quadratic regulator (LQR) is one of the most popular frameworks t...
read it

Approximate Maximum Matching in Random Streams
In this paper, we study the problem of finding a maximum matching in the...
read it

Temporal Network Sampling
Temporal networks representing a stream of timestamped edges are seeming...
read it

From Community to Rolebased Graph Embeddings
Roles are sets of structurally similar nodes that are more similar to no...
read it

Lineartime Hierarchical Community Detection
Community detection in graphs has many important and fundamental applica...
read it

HigherOrder Ranking and Link Prediction: From Closing Triangles to Closing HigherOrder Motifs
In this paper, we introduce the notion of motif closure and describe hig...
read it

Temporal Network Representation Learning
Networks evolve continuously over time with the addition, deletion, and ...
read it

Heterogeneous Network Motifs
Many realworld applications give rise to large heterogeneous networks w...
read it

Higherorder Spectral Clustering for Heterogeneous Graphs
Higherorder connectivity patterns such as small induced subgraphs call...
read it

Higherorder Graph Convolutional Networks
Following the success of deep convolutional networks in various vision a...
read it

Attention Models in Graphs: A Survey
Graphstructured data arise naturally in many different application doma...
read it

Predicting Graph Categories from Structural Properties
Complex networks are often categorized according to the underlying pheno...
read it

HONE: HigherOrder Network Embeddings
This paper describes a general framework for learning HigherOrder Netwo...
read it

Similaritybased Multilabel Learning
Multilabel classification is an important learning problem with many ap...
read it

Inductive Representation Learning in Large Attributed Graphs
Graphs (networks) are ubiquitous and allow us to model entities (nodes) ...
read it

A Framework for Generalizing Graphbased Representation Learning Methods
Random walks are at the heart of many existing deep learning algorithms ...
read it

Network Classification and Categorization
To the best of our knowledge, this paper presents the first largescale ...
read it

Deep Feature Learning for Graphs
This paper presents a general graph representation learning framework ca...
read it

Estimation of Graphlet Statistics
Graphlets are induced subgraphs of a large network and are important for...
read it

Revisiting Role Discovery in Networks: From Node to Edge Roles
Previous work in network analysis has focused on modeling the mixedmemb...
read it

Hybrid CPUGPU Framework for Network Motifs
Massively parallel architectures such as the GPU are becoming increasing...
read it

Relational Similarity Machines
This paper proposes Relational Similarity Machines (RSM): a fast, accura...
read it

Graphlet Decomposition: Framework, Algorithms, and Applications
From social science to biology, numerous applications often rely on grap...
read it

A Webbased Interactive Visual Graph Analytics Platform
This paper proposes a webbased visual graph analytics platform for inte...
read it

Transforming Graph Representations for Statistical Relational Learning
Relational data representations have become an increasingly important to...
read it

Dynamic PageRank using Evolving Teleportation
The importance of nodes in a network constantly fluctuates based on chan...
read it

Representations and Ensemble Methods for Dynamic Relational Classification
Temporal networks are ubiquitous and evolve over time by the addition, d...
read it