Seuraa
Johannes Gasteiger, né Klicpera
Johannes Gasteiger, né Klicpera
Muut nimetJohannes Klicpera, Johannes Gasteiger
Vahvistettu sähköpostiosoite verkkotunnuksessa in.tum.de - Kotisivu
Nimike
Viittaukset
Viittaukset
Vuosi
Predict then Propagate: Graph Neural Networks meet Personalized PageRank
J Gasteiger, A Bojchevski, S Günnemann
International Conference on Learning Representations (ICLR), 2019
885*2019
Directional Message Passing for Molecular Graphs
J Gasteiger, J Groß, S Günnemann
International Conference on Learning Representations (ICLR), 2020
363*2020
Diffusion Improves Graph Learning
J Gasteiger, S Weißenberger, S Günnemann
Advances in Neural Information Processing Systems (NeurIPS), 13354-13366, 2019
319*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
1192020
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
115*2020
GemNet: Universal Directional Graph Neural Networks for Molecules
J Gasteiger, F Becker, S Günnemann
Advances in Neural Information Processing Systems (NeurIPS), 2021
952021
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
412020
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
182019
Collective Robustness Certificates: Exploiting Interdependence in Graph Neural Networks
J Schuchardt, A Bojchevski, J Gasteiger, S Günnemann
International Conference on Learning Representations (ICLR), 2021
132021
Directional Message Passing on Molecular Graphs via Synthetic Coordinates
J Gasteiger, C Yeshwanth, S Günnemann
Advances in Neural Information Processing Systems (NeurIPS), 2021
82021
GemNet-OC: Developing Graph Neural Networks for Large and Diverse Molecular Simulation Datasets
J Gasteiger, M Shuaibi, A Sriram, S Günnemann, ZW Ulissi, CL Zitnick, ...
Transactions on Machine Learning Research, 2022
6*2022
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
52021
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
Machine Learning: Science and Technology 3 (4), 045010, 2022
42022
Nanowire Laser Structure and Fabrication Method
B Mayer, G Koblmueller, J Finley, J Klicpera, G Abstreiter
US Patent App. 15/759,977, 2018
32018
Influence-Based Mini-Batching for Graph Neural Networks
J Gasteiger, C Qian, S Günnemann
Learning on Graphs Conference, 2022
2022
Järjestelmä ei voi suorittaa toimenpidettä nyt. Yritä myöhemmin uudelleen.
Artikkelit 1–15