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).
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Daily Overview |
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Session 3a: Foundation Models for Science
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
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Choose from expert-led talks running simultaneously to explore AI topics that match your interests. | ||
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2:15pm - 2:35pm
Invited talk ID: 407 / a Wed | LAB 14:15 Parallel S 3a: 001 Modalities: Multimodal Data, Simulation Data, Time Series Methods: Foundation Models, Generative Models, Probabilistic Methods Application Domain: Core Machine Learning, Earth & Environment Rethinking the Foundations of Weather and Climate Modelling FZJ, Germany 2:35pm - 2:48pm
ID: 182 / a Wed | LAB 14:15 Parallel S 3a: 002 Modalities: Image Methods: Foundation Models Application Domain: Earth & Environment A Multi-Sensor Foundation Model for Earth Observation 1German Aerospace Center (DLR), Germany; 2Technical University of Munich (TUM), Germany; 3University of the Bundeswehr Munich, Germany; 4Universite Grenoble Alpes, Inria, CNRS, Grenoble INP, LJK, France 2:48pm - 3:01pm
ID: 296 / a Wed | LAB 14:15 Parallel S 3a: 003 Modalities: Image, Multimodal Data, Text Methods: Foundation Models, Generative Models Application Domain: Core Machine Learning, Health OneProtGPT: Bridging Protein Embeddings and Large Language Models for Protein Understanding Jülich Supercomputing Centre, Forschungszentrum Jülich, 52428 Jülich, Germany 3:01pm - 3:14pm
ID: 144 / a Wed | LAB 14:15 Parallel S 3a: 004 Modalities: Text, Other Methods: Foundation Models, Generative Models Application Domain: Health AMPFormer: A Peptide Foundation Model for Antimicrobial Discovery 1Institute of AI for Health, Helmholtz Zentrum Munchen; 2Technical University of Munich, TUM School of Computation, Information and Technology; 3Faculty of Mathematics, Informatics and Mechanics, University of Warsaw; 4University of Pennsylvania, Philadelphia, PA, USA. | ||