Consensus for Collaborative Creation of Risk Maps for COVID-19
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2021 |
Rebollo, M. |
Guided-LORE: Improving LORE with a Focused Search of Neighbours
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2021 |
Maaroof, Najlaa |
Towards Certifying Trustworthy Machine Learning Systems
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2021 |
Yap, Roland H. C. |
Interactive Natural Language Technology for Explainable Artificial Intelligence
|
2021 |
Alonso, Jose M. |
Towards Utilitarian Combinatorial Assignment with Deep Neural Networks and Heuristic Algorithms
|
2021 |
Präntare, Fredrik |
Modelling Agent Policies with Interpretable Imitation Learning
|
2021 |
Bewley, Tom |
Process-To-Text: A Framework for the Quantitative Description of Processes in Natural Language
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2021 |
Fontenla-Seco, Yago |
Underestimation Bias and Underfitting in Machine Learning
|
2021 |
Cunningham, Pádraig |
Safe Learning and Optimization Techniques: Towards a Survey of the State ofthe Art
|
2021 |
Kim, Youngmin |
Assessment of Manifold Unfolding in Trained Deep Neural Network Classifiers
|
2021 |
Pócoš, Stefan |
Election Manipulation on Social Networks with Messages on Multiple Candidates Extended Abstract
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2021 |
Castiglioni, Matteo |
Al-Supported Innovation Monitoring
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2021 |
Braaksma, Barteld |
Transparent Adaptation in Deep Medical Image Diagnosis
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2021 |
Kollias, D. |
Semi-supervised Co-ensembling for AutoML
|
2021 |
Engelen, Jesper E. van |
Two to Trust: AutoML for Safe Modelling and Interpretable Deep Learning for Robustness
|
2021 |
Amirian, Mohammadreza |
Towards Automated GDPR Compliance Checking
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2021 |
Libal, Tomer |
Hybrid AI: The Way Forward in AI by Developing Four Dimensions
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2021 |
Huizing, Albert |
Lab Conditions for Research on Explainable Automated Decisions
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2021 |
Baier, Christel |
An Analysis of Regularized Approaches for Constrained Machine Learning
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2021 |
Lombardi, Michele |
A Causal Framework for Understanding Optimisation Algorithms
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2021 |
Franzin, Alberto |