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Johannes Gasteiger, né Klicpera
Johannes Gasteiger, né Klicpera
Verified email at in.tum.de - Homepage
Title
Cited by
Cited by
Year
Predict then Propagate: Graph Neural Networks meet Personalized PageRank
J Gasteiger, A Bojchevski, S Günnemann
International Conference on Learning Representations (ICLR), 2019
679*2019
Directional Message Passing for Molecular Graphs
J Gasteiger, J Groß, S Günnemann
International Conference on Learning Representations (ICLR), 2020
264*2020
Diffusion Improves Graph Learning
J Gasteiger, S Weißenberger, S Günnemann
Advances in Neural Information Processing Systems (NeurIPS), 13354-13366, 2019
241*2019
Scaling Graph Neural Networks with Approximate PageRank
A Bojchevski, J Klicpera, B Perozzi, A Kapoor, M Blais, B Rózemberczki, ...
26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020
912020
Fast and Uncertainty-Aware Directional Message Passing for Non-Equilibrium Molecules
J Gasteiger, S Giri, JT Margraf, S Günnemann
Machine Learning for Molecules Workshop at NeurIPS, 2020
76*2020
GemNet: Universal Directional Graph Neural Networks for Molecules
J Gasteiger, F Becker, S Günnemann
Advances in Neural Information Processing Systems (NeurIPS), 2021
432021
Efficient Robustness Certificates for Discrete Data: Sparsity-Aware Randomized Smoothing for Graphs, Images and More
A Bojchevski, J Gasteiger, S Günnemann
Thirty-seventh International Conference on Machine Learning (ICML), 2020
332020
Is PageRank All You Need for Scalable Graph Neural Networks?
A Bojchevski, J Klicpera, B Perozzi, M Blais, A Kapoor, M Lukasik, ...
ACM SIGKDD, MLG Workshop, 2019
152019
Collective Robustness Certificates: Exploiting Interdependence in Graph Neural Networks
J Schuchardt, A Bojchevski, J Gasteiger, S Günnemann
International Conference on Learning Representations (ICLR), 2021
92021
Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, and More
J Gasteiger, M Lienen, S Günnemann
International Conference on Machine Learning, 5616-5627, 2021
42021
Nanowire Laser Structure and Fabrication Method
B Mayer, G Koblmueller, J Finley, J Klicpera, G Abstreiter
US Patent App. 15/759,977, 2018
32018
How Robust are Modern Graph Neural Network Potentials in Long and Hot Molecular Dynamics Simulations?
S Stocker, J Gasteiger, F Becker, S Günnemann, JT Margraf
22022
How Do Graph Networks Generalize to Large and Diverse Molecular Systems?
J Gasteiger, M Shuaibi, A Sriram, S Günnemann, Z Ulissi, CL Zitnick, ...
arXiv preprint arXiv:2204.02782, 2022
12022
Directional Message Passing on Molecular Graphs via Synthetic Coordinates
J Gasteiger, C Yeshwanth, S Günnemann
Advances in Neural Information Processing Systems (NeurIPS), 2021
12021
Locality-Based Mini Batching for Graph Neural Networks
J Klicpera, C Qian, S Günnemann
2021
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Articles 1–15