activity
20142025
most citedInterference Effects in Quantum Belief Networks

61 citations · 73 across the 9 of their papers we have counts for

collaborators

6 papers

cs.CV20248 cited

SelfReDepth: Self-Supervised Real-Time Depth Restoration for Consumer-Grade Sensors

Alexandre Duarte, Francisco Fernandes, João M. Pereira +3

Depth maps produced by consumer-grade sensors suffer from inaccurate measurements and missing data from either system or scene-specific sources. Data-driven denoising algorithms ca…

cs.AI20241 cited

Generating Feasible and Plausible Counterfactual Explanations for Outcome Prediction of Business Processes

Alexander Stevens, Chun Ouyang, Johannes De Smedt +1

In recent years, various machine and deep learning architectures have been successfully introduced to the field of predictive process analytics. Nevertheless, the inherent opacity…

cs.CV2023

Integrating Eye-Gaze Data into CXR DL Approaches: A Preliminary study

André Luís, Chihcheng Hsieh, Isabel Blanco Nobre +4

This paper proposes a novel multimodal DL architecture incorporating medical images and eye-tracking data for abnormality detection in chest x-rays. Our results show that applying…

cs.HC20232 cited

Development of an Immersive Virtual Colonoscopy Viewer for Colon Growths Diagnosis

João Serras, Anderson Maciel, Soraia Paulo +4

Desktop-based virtual colonoscopy has been proven to be an asset in the identification of colon anomalies. The process is accurate, although time-consuming. The use of immersive in…

cs.DL20151 cited

Uma análise bibliométrica do Congresso Nacional de Bibliotecários, Arquivistas e Documentalistas (1985-2012)

Silvana Roque de Oliveira, Catarina Moreira, José Borbinha +1

This article is the first bibliometric analysis of the 708 lectures published by The Librarians and Archivists National Congress between 1985 and 2012, having been developed marker…

cs.AI201461 cited

Interference Effects in Quantum Belief Networks

Catarina Moreira, Andreas Wichert

Probabilistic graphical models such as Bayesian Networks are one of the most powerful structures known by the Computer Science community for deriving probabilistic inferences. Howe…