19 citations · 65 across the 9 of their papers we have counts for
9 papers
Optimal Embedding Guided Negative Sample Generation for Knowledge Graph Link Prediction
Makoto Takamoto, Daniel Oñoro-Rubio, Wiem Ben Rim +2
Knowledge graph embedding (KGE) models encode the structural information of knowledge graphs to predicting new links. Effective training of these models requires distinguishing bet…
Learning Sparsity of Representations with Discrete Latent Variables
Zhao Xu, Daniel Onoro Rubio, Giuseppe Serra +1
Deep latent generative models have attracted increasing attention due to the capacity of combining the strengths of deep learning and probabilistic models in an elegant way. The da…
A Relational-learning Perspective to Multi-label Chest X-ray Classification
Anjany Sekuboyina, Daniel Oñoro-Rubio, Jens Kleesiek +1
Multi-label classification of chest X-ray images is frequently performed using discriminative approaches, i.e. learning to map an image directly to its binary labels. Such approach…
MMKG: Multi-Modal Knowledge Graphs
Ye Liu, Hui Li, Alberto Garcia-Duran +3
We present MMKG, a collection of three knowledge graphs that contain both numerical features and (links to) images for all entities as well as entity alignments between pairs of KG…
Contextual Hourglass Networks for Segmentation and Density Estimation
Daniel Oñoro-Rubio, Mathias Niepert
Hourglass networks such as the U-Net and V-Net are popular neural architectures for medical image segmentation and counting problems. Typical instances of hourglass networks contai…
Learning Short-Cut Connections for Object Counting
Daniel Oñoro-Rubio, Mathias Niepert, Roberto J. López-Sastre
Object counting is an important task in computer vision due to its growing demand in applications such as traffic monitoring or surveillance. In this paper, we consider object coun…
The challenge of simultaneous object detection and pose estimation: a comparative study
Daniel Oñoro-Rubio, Roberto J. López-Sastre, Carolina Redondo-Cabrera +1
Detecting objects and estimating their pose remains as one of the major challenges of the computer vision research community. There exists a compromise between localizing the objec…
TransRev: Modeling Reviews as Translations from Users to Items
Alberto Garcia-Duran, Roberto Gonzalez, Daniel Onoro-Rubio +2
The text of a review expresses the sentiment a customer has towards a particular product. This is exploited in sentiment analysis where machine learning models are used to predict…
Answering Visual-Relational Queries in Web-Extracted Knowledge Graphs
Daniel Oñoro-Rubio, Mathias Niepert, Alberto García-Durán +2
A visual-relational knowledge graph (KG) is a multi-relational graph whose entities are associated with images. We explore novel machine learning approaches for answering visual-re…