189 citations · 584 across the 63 of their papers we have counts for
9 papers · 1 filter
Principled Multilayer Network Embedding
Weiyi Liu, Pin-Yu Chen, Sailung Yeung +2
Multilayer network analysis has become a vital tool for understanding different relationships and their interactions in a complex system, where each layer in a multilayer network d…
Learning Graph Topological Features via GAN
Weiyi Liu, Hal Cooper, Min Hwan Oh +4
Inspired by the generation power of generative adversarial networks (GANs) in image domains, we introduce a novel hierarchical architecture for learning characteristic topological…
Full-Network Embedding in a Multimodal Embedding Pipeline
Armand Vilalta, Dario Garcia-Gasulla, Ferran Parés +4
The current state-of-the-art for image annotation and image retrieval tasks is obtained through deep neural networks, which combine an image representation and a text representatio…
Building Graph Representations of Deep Vector Embeddings
Dario Garcia-Gasulla, Armand Vilalta, Ferran Parés +5
Patterns stored within pre-trained deep neural networks compose large and powerful descriptive languages that can be used for many different purposes. Typically, deep network repre…
Can GAN Learn Topological Features of a Graph?
Weiyi Liu, Pin-Yu Chen, Hal Cooper +3
This paper is first-line research expanding GANs into graph topology analysis. By leveraging the hierarchical connectivity structure of a graph, we have demonstrated that generativ…
An Out-of-the-box Full-network Embedding for Convolutional Neural Networks
Dario Garcia-Gasulla, Armand Vilalta, Ferran Parés +5
Transfer learning for feature extraction can be used to exploit deep representations in contexts where there is very few training data, where there are limited computational resour…
Medical Text Classification using Convolutional Neural Networks
Mark Hughes, Irene Li, Spyros Kotoulas +1
We present an approach to automatically classify clinical text at a sentence level. We are using deep convolutional neural networks to represent complex features. We train the netw…
Fluid Communities: A Competitive, Scalable and Diverse Community Detection Algorithm
Ferran Parés, Dario Garcia-Gasulla, Armand Vilalta +5
We introduce a community detection algorithm (Fluid Communities) based on the idea of fluids interacting in an environment, expanding and contracting as a result of that interactio…
On the Behavior of Convolutional Nets for Feature Extraction
Dario Garcia-Gasulla, Ferran Parés, Armand Vilalta +5
Deep neural networks are representation learning techniques. During training, a deep net is capable of generating a descriptive language of unprecedented size and detail in machine…