Conference Agenda
Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
|
Daily Overview |
| Session | ||
Session 4b: Infrastructure & Tools
Session Topics: Agentic AI, Foundation Models, Generative Models, Graph Neural Networks, Physics-informed Machine Learning, Reinforcement Learning, Probabilistic Methods, Uncertainty Quantification, Audio, Other, Graphs, Image, Multimodal Data, Simulation Data, Tabular Data, Text, Time Series, Video, Other, Core Machine Learning, Aeronautics, Space & Transport, Energy, Earth & Environment, Health, Information, Matter
| ||
| Session Abstract | ||
|
Choose from expert-led talks running simultaneously to explore AI topics that match your interests. | ||
    | ||
9:00am - 9:12am
ID: 1161 / Thu | GERN 9h Parallel S 4b: 001 Modalities: Image Methods: Other Application Domain: Health AI-assisted Labeling and its Pitfalls: A Case Study in Electron Microscopy Segmentation 1Helmholtz AI, Helmholtz Center Munich, Germany; 2Institute of Toxicology and Environmental Hygiene, TUM School of Medicine and Health, Technical University of Munich, Germany; 3Institute of Molecular Toxicology and Pharmacology, Helmholtz Center Munich, Germany 9:12am - 9:24am
ID: 149 / Thu | GERN 9h Parallel S 4b: 002 Modalities: Image Methods: Other Application Domain: Health A decentralized Swarm Learning framework for 90-Day outcome prediction for acute ischaemic stroke 1DZNE, Germany; 2CISPA, Germany 9:24am - 9:36am
ID: 228 / Thu | GERN 9h Parallel S 4b: 003 Modalities: Graphs, Image, Time Series Methods: Graph Neural Networks Application Domain: Matter Microsecond Latency Graph Neural Network Inference on Point Clouds Karlsruhe Institute of Technology, Germany 9:36am - 9:48am
ID: 146 / Thu | GERN 9h Parallel S 4b: 004 Modalities: Graphs, Simulation Data Methods: Agentic AI, Foundation Models, Generative Models, Graph Neural Networks, Physics-informed Machine Learning, Reinforcement Learning Application Domain: Core Machine Learning, Aeronautics, Space & Transport, Energy, Matter GENIUS: An Agentic AI Framework for Autonomous Design and Execution of Simulation Protocols 1Karlsruhe Institute of Technology, Germany; 2Helmholtz-Zentrum Hereon 9:48am - 10:00am
ID: 137 / Thu | GERN 9h Parallel S 4b: 005 Modalities: Image Methods: Foundation Models Application Domain: Core Machine Learning, Information The Road to Exascale: Lessons Learned from Scaling a Scientific AI Workflow to 16,384 GPUs 1Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich (FZJ), Germany; 2Helmholtz AI, Forschungszentrum Jülich (FZJ), Germany; 3Jülich Supercomputing Centre (JSC), Forschungszentrum Jülich, Germany; 4German BioImaging, Gesellschaft für Mikroskopie und Bildanalyse e.V, Konstanz, Germany; 5Cécile & Oskar Vogt Institute for Brain Research, University Hospital Düsseldorf, Germany; 6Computer Vision, Institute for Computational Visualistics, University of Koblenz, Germany | ||