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Clemens Damke

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2024
[c4]
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  - conf/pkdd/DamkeH24
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Clemens Damke, Eyke Hüllermeier:
CUQ-GNN: Committee-Based Graph Uncertainty Quantification Using Posterior Networks. ECML/PKDD (8) 2024: 306-323
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  - journals/corr/abs-2406-04041
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Clemens Damke, Eyke Hüllermeier:
Linear Opinion Pooling for Uncertainty Quantification on Graphs. CoRR abs/2406.04041 (2024)
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  - journals/corr/abs-2409-04159
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Clemens Damke, Eyke Hüllermeier:
CUQ-GNN: Committee-based Graph Uncertainty Quantification using Posterior Networks. CoRR abs/2409.04159 (2024)
2023
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Anna-Katharina Wickert, Clemens Damke, Lars Baumgärtner, Eyke Hüllermeier, Mira Mezini:
UnGoML: Automated Classification of unsafe Usages in Go. MSR 2023: 309-321
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  - journals/corr/abs-2306-00694
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Anna-Katharina Wickert, Clemens Damke, Lars Baumgärtner, Eyke Hüllermeier, Mira Mezini:
UNGOML: Automated Classification of unsafe Usages in Go. CoRR abs/2306.00694 (2023)
2021
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Clemens Damke, Eyke Hüllermeier:
Ranking Structured Objects with Graph Neural Networks. DS 2021: 166-180
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  - journals/corr/abs-2104-08869
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Clemens Damke, Eyke Hüllermeier:
Ranking Structured Objects with Graph Neural Networks. CoRR abs/2104.08869 (2021)
2020
[c1]
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Clemens Damke, Vitalik Melnikov, Eyke Hüllermeier:
A Novel Higher-order Weisfeiler-Lehman Graph Convolution. ACML 2020: 49-64
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  - journals/corr/abs-2007-00346
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Clemens Damke, Vitalik Melnikov, Eyke Hüllermeier:
A Novel Higher-order Weisfeiler-Lehman Graph Convolution. CoRR abs/2007.00346 (2020)

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