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Found 6 papers, 3 papers with code
Limitations and Alternatives for the Evaluation of Large-scale Link Prediction
Link prediction, the problem of identifying missing links among a set of inter-related data entities, is a popular field of research due to its application to graph-like domains.
On the Behavior of Convolutional Nets for Feature Extraction
We seek to provide new insights into the behavior of CNN features, particularly the ones from convolutional layers, as this can be relevant for their application to knowledge representation and reasoning.
Fluid Communities: A Competitive, Scalable and Diverse Community Detection Algorithm
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 interaction.
Data Structures and Algorithms Social and Information Networks Physics and Society
MetH: A family of high-resolution and variable-shape image challenges
In sight of the increasing importance of problems that can benefit from exploiting high-resolution (HR) and variable-shape, and with the goal of promoting research in that direction, we introduce a new family of datasets (MetH).
Random Forest as a Tumour Genetic Marker Extractor
Finding tumour genetic markers is essential to biomedicine due to their relevance for cancer detection and therapy development.
The MAMe Dataset: On the relevance of High Resolution and Variable Shape image properties
In this work we introduce the MAMe dataset, an image classification dataset with remarkable high resolution and variable shape properties.
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Image Classification
on MAMe
