41 citations · 132 across the 15 of their papers we have counts for
16 papers
Trade-offs in Financial AI: Explainability in a Trilemma with Accuracy and Compliance
Patricia Marcella Evite, Ekaterina Svetlova, Doina Bucur
As Artificial Intelligence (AI) becomes increasingly embedded in financial decision-making, the opacity of complex models presents significant challenges for professionals and regu…
gFlora: a topology-aware method to discover functional co-response groups in soil microbial communities
Nan Chen, Merlijn Schram, Doina Bucur
We aim to learn the functional co-response group: a group of taxa whose co-response effect (the representative characteristic of the group showing the total topological abundance o…
Learning the mechanisms of network growth
Lourens Touwen, Doina Bucur, Remco van der Hofstad +2
We propose a novel model-selection method for dynamic networks. Our approach involves training a classifier on a large body of synthetic network data. The data is generated by simu…
Parallels in the symbolism of star constellations
Doina Bucur
We answer the question whether, when forming constellations in the night sky, people in astronomical cultures around the world and through time consistently imagined and assigned t…
Understanding Sparse Neural Networks from their Topology via Multipartite Graph Representations
Elia Cunegatti, Matteo Farina, Doina Bucur +1
Pruning-at-Initialization (PaI) algorithms provide Sparse Neural Networks (SNNs) which are computationally more efficient than their dense counterparts, and try to avoid performanc…
Large-scale multi-objective influence maximisation with network downscaling
Elia Cunegatti, Giovanni Iacca, Doina Bucur
Finding the most influential nodes in a network is a computationally hard problem with several possible applications in various kinds of network-based problems. While several metho…
Automated fault tree learning from continuous-valued sensor data: a case study on domestic heaters
Bart Verkuil, Carlos E. Budde, Doina Bucur
Many industrial sectors have been collecting big sensor data. With recent technologies for processing big data, companies can exploit this for automatic failure detection and preve…
Bias in Automated Image Colorization: Metrics and Error Types
Frank Stapel, Floris Weers, Doina Bucur
We measure the color shifts present in colorized images from the ADE20K dataset, when colorized by the automatic GAN-based DeOldify model. We introduce fine-grained local and regio…
Look back, look around: a systematic analysis of effective predictors for new outlinks in focused Web crawling
Thi Kim Nhung Dang, Doina Bucur, Berk Atil +4
Small and medium enterprises rely on detailed Web analytics to be informed about their market and competition. Focused crawlers meet this demand by crawling and indexing specific p…
The network signature of constellation line figures
Doina Bucur
In traditional astronomies across the world, groups of stars in the night sky were linked into constellations -- symbolic representations rich in meaning and with practical roles.…
Dynamic detection of mobile malware using smartphone data and machine learning
J. S. Panman de Wit, J. van der Ham, D. Bucur
Mobile malware are malicious programs that target mobile devices. They are an increasing problem, as seen in the rise of detected mobile malware samples per year. The number of act…
Independent Prototype Propagation for Zero-Shot Compositionality
Frank Ruis, Gertjan Burghouts, Doina Bucur
Humans are good at compositional zero-shot reasoning; someone who has never seen a zebra before could nevertheless recognize one when we tell them it looks like a horse with black…
Top influencers can be identified universally by combining classical centralities
Doina Bucur
Information flow, opinion, and epidemics spread over structured networks. When using individual node centrality indicators to predict which nodes will be among the top influencers…
Fault Trees from Data: Efficient Learning with an Evolutionary Algorithm
Alexis Linard, Doina Bucur, Marielle Stoelinga
Cyber-physical systems come with increasingly complex architectures and failure modes, which complicates the task of obtaining accurate system reliability models. At the same time,…
Beyond ranking nodes: Predicting epidemic outbreak sizes by network centralities
Doina Bucur, Petter Holme
Identifying important nodes for disease spreading is a central topic in network epidemiology. We investigate how well the position of a node, characterized by standard network meas…
Optimizing groups of colluding strong attackers in mobile urban communication networks with evolutionary algorithms
D. Bucur, G. Iacca, M. Gaudesi +2
In novel forms of the Social Internet of Things, any mobile user within communication range may help routing messages for another user in the network. The resulting message deliver…