most citedFull-Network Embedding in a Multimodal Embedding Pipeline

5 citations · 16 across the 5 of their papers we have counts for

collaborators

5 papers

q-bio.GN2019

Random Forest as a Tumour Genetic Marker Extractor

Raquel Pérez-Arnal, Dario Garcia-Gasulla, David Torrents +4

Finding tumour genetic markers is essential to biomedicine due to their relevance for cancer detection and therapy development. In this paper, we explore a recently released datase…

cs.CV2017★ 5 cited

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…

cs.NE2017★ 4 cited

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…

cs.DS2017★ 4 cited

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…

cs.NE2017★ 3 cited

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…