04.11.2019
MCML at ACM SIGSPATIAL 2019
One Accepted Paper
27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Chicago, ILL, USA, Nov 05-08, 2019
We are happy to announce that MCML researchers have contributed a total of 1 paper to ACM SIGSPATIAL 2019. Congrats to our researchers!
Main Track (1 paper)
F. Borutta • S. Schmoll • S. Friedl
Optimizing the Spatio-Temporal Resource Search Problem with Reinforcement Learning.
ACM SIGSPATIAL 2019 - 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. Chicago, ILL, USA, Nov 05-08, 2019. DOI
Optimizing the Spatio-Temporal Resource Search Problem with Reinforcement Learning.
ACM SIGSPATIAL 2019 - 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. Chicago, ILL, USA, Nov 05-08, 2019. DOI
Related
31.07.2026
Benedikt Wiestler: We Want to Build a Time Machine
MCML PI Benedikt Wiestler explains how AI models help to develop specific strategies in clinical therapy for brain tumor patients.
28.07.2026
Gaps in the Benchmark: Why Medical AI Fails in the Real World
MCML researchers show in Nature Health how dynamic red teaming exposes hidden weaknesses in Medical AI beyond static benchmarks.