21.08.2020
MCML at KDD 2020
Two Accepted Papers
26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Diego, California, USA, Aug 23-27, 2020
We are happy to announce that MCML researchers have contributed a total of 2 papers to KDD 2020. Congrats to our researchers!
Main Track (2 papers)
C. Plant • S. Biedermann • C. Böhm
Data Compression as a Comprehensive Framework for Graph Drawing and Representation Learning.
KDD 2020 - 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. San Diego, California, USA, Aug 23-27, 2020. DOI
Data Compression as a Comprehensive Framework for Graph Drawing and Representation Learning.
KDD 2020 - 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. San Diego, California, USA, Aug 23-27, 2020. DOI
D. Zügner • S. Günnemann
Certifiable Robustness of Graph Convolutional Networks under Structure Perturbation.
KDD 2020 - 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. San Diego, California, USA, Aug 23-27, 2020. DOI
Certifiable Robustness of Graph Convolutional Networks under Structure Perturbation.
KDD 2020 - 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. San Diego, California, USA, Aug 23-27, 2020. DOI
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Vincent Fortuin Receives ERC Starting Grant for Reliable Small-Data AI
MCML PI Vincent Fortuin receives an ERC Starting Grant for AutoBayes, advancing reliable AI methods for learning from small datasets.
