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  1. 7 de may. de 2024 · Prof. Dr. Johannes Margraf Joins University of Bayreuth as Professor October 04, 2023 Prof. Dr. Johannes Margraf, a distinguished researcher and Group Leader at the Fritz-Haber-Institut der Max-Planck-Gesellschaft (FHI) in Berlin, has been appointed as a Professor at the University of Bayreuth.

  2. 7 de may. de 2024 · Prof. Dr. Johannes Margraf, ein renommierter Forscher und Gruppenleiter am Fritz-Haber-Institut der Max-Planck-Gesellschaft (FHI) in Berlin, wurde zum Professor an der Universität Bayreuth ernannt. Die Zusammenarbeit von Prof. Dr. Margraf mit der Universität begann offiziell im September und markiert einen bedeutenden Schritt in ...

  3. 1 de may. de 2024 · 20.03.2024 - El Prof. Dr. Johannes Margraf y un equipo de científicos han desarrollado un método prometedor para mejorar la eficacia de los electrocatalizadores. Mediante simulaciones e inteligencia artificial, los investigadores han desarrollado un programa informático capaz de optimizar simultáneamente ...

  4. 7 de may. de 2024 · Gasteiger, J., Giri, S., Margraf, J. T. & Günnemann, S. Fast and uncertainty-aware directional message passing for non-equilibrium molecules. Preprint at https://arxiv.org/abs/2011.14115 (2022).

  5. 21 de may. de 2024 · Host: Hendrik Heenen, Miguel Caro, Gabor Csanyi, Albert Bartok-Partay, Johannes Margraf, Giulia Glorani The countdown has begun for the upcoming CECAM Node Workshop: "GAP/(M)ACE Developers & Users Meeting 2024", which will take place from the 17th to the 20th of September at the Institute of Computer Science of the Free University of ...

  6. 19 de may. de 2024 · FIG. 2: Plots of predicted formation energy and bandgap versus target for CGCNN, MEGNet, and CTGNN models, respectively. the upper and right part are the target and prediction data distribution. - "CTGNN: Crystal Transformer Graph Neural Network for Crystal Material Property Prediction"

  7. 13 de may. de 2024 · Dr. Johannes Margraf (FHI Berlin) Integrating Machine Learning and Electronic Structure Theory. 15.02.2023: Dr. Tobias Gensch (TU Berlin) Data-driven workflows to guide experiments and understand ligand effects in catalysis. 08.02.2023: Prof. Dr. Christoph Bannwarth (RWTH Aachen)