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)
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
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
Related
24.02.2026
Cosmology: Measuring the Expansion of the Universe With Cosmic Fireworks
Daniel Gruen leads LMU’s campaign on rare SN Winny to refine the Hubble constant and address the Hubble tension in cosmology.
19.02.2026
COSMOS – Teaching Vision-Language Models to Look Beyond the Obvious
Presented at CVPR 2025, COSMOS shows how smarter training helps VLMs learn from details and context, improving AI understanding without larger models.
05.02.2026
Daniel Rückert and Fabian Theis Awarded Google.org AI for Science Grant
Daniel Rueckert and Fabian Theis receive Google.org AI funding to develop multiscale AI models for biomedical disease simulation.