Search Results for author:
Found 5 papers, 1 papers with code
Data-driven Intra-Autonomous Systems Graph Generator
This paper introduces a novel deep-learning-based generator of synthetic graphs representing intra-autonomous in the Internet, named Deep-Generative Graphs for the Internet (DGGI).
Measuring economic activity from space: a case study using flying airplanes and COVID-19
This work introduces a novel solution to measure economic activity through remote sensing for a wide range of spatial areas.
Multimodal Prediction based on Graph Representations
Performed experiments in the context of multiple multimodal and visual datasets, as well as several descriptors and retrieval models, demonstrate that our learning model is highly effective for different prediction scenarios involving visual, textual, and multimodal features, yielding better effectiveness than state-of-the-art methods.
Fusion vectors: Embedding Graph Fusions for Efficient Unsupervised Rank Aggregation
We propose an innovative rank aggregation function that is unsupervised, intrinsically multimodal, and targeted for fast retrieval and top effectiveness performance.
Unsupervised Graph-based Rank Aggregation for Improved Retrieval
This paper presents a robust and comprehensive graph-based rank aggregation approach, used to combine results of isolated ranker models in retrieval tasks.
