9 citations · 15 across the 4 of their papers we have counts for
7 papers
Adaptive Neural Message Passing for Inductive Learning on Hypergraphs
Devanshu Arya, Deepak K. Gupta, Stevan Rudinac +1
Graphs are the most ubiquitous data structures for representing relational datasets and performing inferences in them. They model, however, only pairwise relations between nodes an…
HyperSAGE: Generalizing Inductive Representation Learning on Hypergraphs
Devanshu Arya, Deepak K. Gupta, Stevan Rudinac +1
Graphs are the most ubiquitous form of structured data representation used in machine learning. They model, however, only pairwise relations between nodes and are not designed for…
Echo Chambers Exist! (But They're Full of Opposing Views)
Jonathan Bright, Nahema Marchal, Bharath Ganesh +1
The theory of echo chambers, which suggests that online political discussions take place in conditions of ideological homogeneity, has recently gained popularity as an explanation…
HyperLearn: A Distributed Approach for Representation Learning in Datasets With Many Modalities
Devanshu Arya, Stevan Rudinac, Marcel Worring
Multimodal datasets contain an enormous amount of relational information, which grows exponentially with the introduction of new modalities. Learning representations in such a scen…
Interactive Search and Exploration in Online Discussion Forums Using Multimodal Embeddings
Iva Gornishka, Stevan Rudinac, Marcel Worring
In this paper we present a novel interactive multimodal learning system, which facilitates search and exploration in large networks of social multimedia users. It allows the analys…
Multimodal Classification of Urban Micro-Events
Maarten Sukel, Stevan Rudinac, Marcel Worring
In this paper we seek methods to effectively detect urban micro-events. Urban micro-events are events which occur in cities, have limited geographical coverage and typically affect…