Adrien Pavão

Orcid: 0000-0001-7374-5095

According to our database1, Adrien Pavão authored at least 17 papers between 2019 and 2026.

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

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Benchmarking Temporal Web3 Intelligence: Lessons from the FinSurvival 2025 Challenge.
Proceedings of the Companion Proceedings of the ACM Web Conference 2026, 2026

2025
We are not able to identify AI-generated images.
CoRR, December, 2025

2024
AI Competitions and Benchmarks, Practical issues: Proposals, grant money, sponsors, prizes, dissemination, publicity.
CoRR, 2024

2023
Methodology for Design and Analysis of Machine Learning Competitions. (Méthodologie pour la conception et l'analyse de compétitions en apprentissage automatique).
PhD thesis, 2023

CodaLab Competitions: An Open Source Platform to Organize Scientific Challenges.
J. Mach. Learn. Res., 2023

2022
Codabench: Flexible, easy-to-use, and reproducible meta-benchmark platform.
Patterns, 2022

Reinforcement learning for Energies of the future and carbon neutrality: a Challenge Design.
CoRR, 2022

Filtering participants improves generalization in competitions and benchmarks.
Proceedings of the 30th European Symposium on Artificial Neural Networks, 2022

2021
Winning Solutions and Post-Challenge Analyses of the ChaLearn AutoDL Challenge 2019.
IEEE Trans. Pattern Anal. Mach. Intell., 2021


Judging competitions and benchmarks: a candidate election approach.
Proceedings of the 29th European Symposium on Artificial Neural Networks, 2021

2020
Towards automated computer vision: analysis of the AutoCV challenges 2019.
Pattern Recognit. Lett., 2020

Generation and evaluation of privacy preserving synthetic health data.
Neurocomputing, 2020

2019
Synthetic Event Time Series Health Data Generation.
CoRR, 2019

Towards Automated Deep Learning: Analysis of the AutoDL challenge series 2019.
Proceedings of the NeurIPS 2019 Competition and Demonstration Track, 2019

Privacy Preserving Synthetic Health Data.
Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019

Assessing privacy and quality of synthetic health data.
Proceedings of the Conference on Artificial Intelligence for Data Discovery and Reuse, 2019


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