Johannes Gasteiger
Publications by Year
Research Areas
Machine Learning in Materials Science, Computational Drug Discovery Methods, Advanced Graph Neural Networks, Topic Modeling, Adversarial Robustness in Machine Learning
Most-Cited Works
- → Predict then Propagate: Graph Neural Networks meet Personalized PageRank(2018)431 cited
- → Scaling Graph Neural Networks with Approximate PageRank(2020)351 cited
- → Directional Message Passing for Molecular Graphs(2020)345 cited
- → Diffusion Improves Graph Learning(2019)175 cited
- → Fast and Uncertainty-Aware Directional Message Passing for Non-Equilibrium Molecules(2020)160 cited
- → GemNet: Universal Directional Graph Neural Networks for Molecules(2021)127 cited
- → How robust are modern graph neural network potentials in long and hot molecular dynamics simulations?(2022)70 cited
- → GemNet-OC: Developing Graph Neural Networks for Large and Diverse Molecular Simulation Datasets(2022)54 cited
- → Directional Message Passing on Molecular Graphs via Synthetic Coordinates(2021)11 cited