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A mutually exciting latent space Hawkes process model for continuous-time networks
Networks and temporal point processes serve as fundamental building blocks for modeling
complex dynamic relational data in various domains. We propose the latent space Hawkes …
complex dynamic relational data in various domains. We propose the latent space Hawkes …
Intensity profile projection: A framework for continuous-time representation learning for dynamic networks
We present a new representation learning framework, Intensity Profile Projection, for
continuous-time dynamic network data. Given triples $(i, j, t) $, each representing a time …
continuous-time dynamic network data. Given triples $(i, j, t) $, each representing a time …
Direct embedding of temporal network edges via time-decayed line graphs
Temporal networks model a variety of important phenomena involving timed interactions
between entities. Existing methods for machine learning on temporal networks generally …
between entities. Existing methods for machine learning on temporal networks generally …
The multivariate community hawkes model for dependent relational events in continuous-time networks
The stochastic block model (SBM) is one of the most widely used generative models for
network data. Many continuous-time dynamic network models are built upon the same …
network data. Many continuous-time dynamic network models are built upon the same …
Continuous-time graph representation with sequential survival process
Over the past two decades, there has been a tremendous increase in the growth of
representation learning methods for graphs, with numerous applications across various …
representation learning methods for graphs, with numerous applications across various …
Piecewise-velocity model for learning continuous-time dynamic node representations
Networks have become indispensable and ubiquitous structures in many fields to model the
interactions among different entities, such as friendship in social networks or protein …
interactions among different entities, such as friendship in social networks or protein …
Generalizability and usefulness of artificial intelligence for skin cancer diagnostics: an algorithm validation study
Background Artificial intelligence can be trained to outperform dermatologists in image‐
based skin cancer diagnostics. However, the networks' sensitivity to biases and overfitting …
based skin cancer diagnostics. However, the networks' sensitivity to biases and overfitting …
The hawkes edge partition model for continuous-time event-based temporal networks
We propose a novel probabilistic framework to model continuously generated interaction
events data. Our goal is to infer the\emph {implicit} community structure underlying the …
events data. Our goal is to infer the\emph {implicit} community structure underlying the …
Time to Cite: Modeling Citation Networks using the Dynamic Impact Single-Event Embedding Model
Understanding the structure and dynamics of scientific research, ie, the science of science
(SciSci), has become an important area of research in order to address imminent questions …
(SciSci), has become an important area of research in order to address imminent questions …
Wasserstein generative adversarial networks for modeling marked events
Marked temporal events are ubiquitous in several areas, where the events' times and marks
(types) are usually interrelated. Point processes and their non-functional variations using …
(types) are usually interrelated. Point processes and their non-functional variations using …