Mario Alfonso Prado-Romero

Orcid: 0000-0002-0491-3515

Affiliations:
  • University of Havana, Cuba


According to our database1, Mario Alfonso Prado-Romero authored at least 12 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Online presence:

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Bibliography

2024
Robust Stochastic Graph Generator for Counterfactual Explanations.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Developing and Evaluating Graph Counterfactual Explanation with GRETEL.
Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

Revisiting CounteRGAN for Counterfactual Explainability of Graphs.
Proceedings of the First Tiny Papers Track at ICLR 2023, 2023

2022
A Survey on Graph Counterfactual Explanations: Definitions, Methods, Evaluation.
CoRR, 2022

GRETEL: A unified framework for Graph Counterfactual Explanation Evaluation.
CoRR, 2022

GRETEL: Graph Counterfactual Explanation Evaluation Framework.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Ensemble Approaches for Graph Counterfactual Explanations.
Proceedings of the 3rd Italian Workshop on Explainable Artificial Intelligence co-located with 21th International Conference of the Italian Association for Artificial Intelligence(AIxIA 2022), Udine, Italy, November 28, 2022

2019
TSTM: A Model to Predict Topics' Popularity in News Providers.
Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2019

2018
Identifying Twitter Users Influence and Open Mindedness Using Anomaly Detection.
Proceedings of the Progress in Artificial Intelligence and Pattern Recognition, 2018

2017
Discovering Bitcoin Mixing Using Anomaly Detection.
Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2017

2016
Detecting contextual collective anomalies at a Glance.
Proceedings of the 23rd International Conference on Pattern Recognition, 2016

Community Feature Selection for Anomaly Detection in Attributed Graphs.
Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2016


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