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ORCIDStephan Günnemann
- > Home > Persons > Stephan Günnemann
Publications
- 2024
[i145]Simon Geisler, Tom Wollschläger, M. H. I. Abdalla, Johannes Gasteiger, Stephan Günnemann:
Attacking Large Language Models with Projected Gradient Descent. CoRR abs/2402.09154 (2024)- 2023
- [c154]Arthur Kosmala, Johannes Gasteiger, Nicholas Gao, Stephan Günnemann:
Ewald-based Long-Range Message Passing for Molecular Graphs. ICML 2023: 17544-17563 - [i119]Jan Schuchardt, Aleksandar Bojchevski, Johannes Gasteiger, Stephan Günnemann:
Collective Robustness Certificates: Exploiting Interdependence in Graph Neural Networks. CoRR abs/2302.02829 (2023) - [i117]Arthur Kosmala, Johannes Gasteiger, Nicholas Gao, Stephan Günnemann:
Ewald-based Long-Range Message Passing for Molecular Graphs. CoRR abs/2303.04791 (2023) - 2022
- [j21]Sina Stocker, Johannes Gasteiger
, Florian Becker, Stephan Günnemann, Johannes T. Margraf:
How robust are modern graph neural network potentials in long and hot molecular dynamics simulations? Mach. Learn. Sci. Technol. 3(4): 45010 (2022) - [j19]Johannes Gasteiger, Muhammed Shuaibi, Anuroop Sriram, Stephan Günnemann, Zachary W. Ulissi, C. Lawrence Zitnick, Abhishek Das:
GemNet-OC: Developing Graph Neural Networks for Large and Diverse Molecular Simulation Datasets. Trans. Mach. Learn. Res. 2022 (2022) - [c128]Johannes Gasteiger, Chendi Qian, Stephan Günnemann:
Influence-Based Mini-Batching for Graph Neural Networks. LoG 2022: 9 - [i83]Johannes Gasteiger, Muhammed Shuaibi, Anuroop Sriram, Stephan Günnemann, Zachary W. Ulissi, C. Lawrence Zitnick, Abhishek Das:
How Do Graph Networks Generalize to Large and Diverse Molecular Systems? CoRR abs/2204.02782 (2022) - [i68]Johannes Gasteiger, Chendi Qian, Stephan Günnemann:
Influence-Based Mini-Batching for Graph Neural Networks. CoRR abs/2212.09083 (2022) - 2021
- [c118]Jan Schuchardt, Aleksandar Bojchevski, Johannes Klicpera, Stephan Günnemann:
Collective Robustness Certificates: Exploiting Interdependence in Graph Neural Networks. ICLR 2021 - [c115]Johannes Klicpera, Marten Lienen, Stephan Günnemann:
Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, and More. ICML 2021: 5616-5627 - [c111]Johannes Gasteiger, Florian Becker, Stephan Günnemann:
GemNet: Universal Directional Graph Neural Networks for Molecules. NeurIPS 2021: 6790-6802 - [c109]Johannes Gasteiger, Chandan Yeshwanth, Stephan Günnemann:
Directional Message Passing on Molecular Graphs via Synthetic Coordinates. NeurIPS 2021: 15421-15433 - [i62]Johannes Gasteiger, Florian Becker, Stephan Günnemann:
GemNet: Universal Directional Graph Neural Networks for Molecules. CoRR abs/2106.08903 (2021) - [i56]Johannes Klicpera, Marten Lienen, Stephan Günnemann:
Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, and More. CoRR abs/2107.06876 (2021) - [i43]Johannes Klicpera, Chandan Yeshwanth, Stephan Günnemann:
Directional Message Passing on Molecular Graphs via Synthetic Coordinates. CoRR abs/2111.04718 (2021) - 2020
- [c99]Johannes Klicpera, Janek Groß, Stephan Günnemann:
Directional Message Passing for Molecular Graphs. ICLR 2020 - [c96]Aleksandar Bojchevski, Johannes Klicpera, Stephan Günnemann:
Efficient Robustness Certificates for Discrete Data: Sparsity-Aware Randomized Smoothing for Graphs, Images and More. ICML 2020: 1003-1013 - [c94]Aleksandar Bojchevski, Johannes Klicpera, Bryan Perozzi, Amol Kapoor, Martin Blais, Benedek Rózemberczki, Michal Lukasik, Stephan Günnemann:
Scaling Graph Neural Networks with Approximate PageRank. KDD 2020: 2464-2473 - [i42]Johannes Klicpera, Janek Groß, Stephan Günnemann:
Directional Message Passing for Molecular Graphs. CoRR abs/2003.03123 (2020) - [i37]Aleksandar Bojchevski, Johannes Klicpera, Bryan Perozzi, Amol Kapoor, Martin Blais, Benedek Rózemberczki, Michal Lukasik, Stephan Günnemann:
Scaling Graph Neural Networks with Approximate PageRank. CoRR abs/2007.01570 (2020) - [i34]Aleksandar Bojchevski, Johannes Klicpera, Stephan Günnemann:
Efficient Robustness Certificates for Discrete Data: Sparsity-Aware Randomized Smoothing for Graphs, Images and More. CoRR abs/2008.12952 (2020) - [i28]Johannes Klicpera, Shankari Giri, Johannes T. Margraf, Stephan Günnemann:
Fast and Uncertainty-Aware Directional Message Passing for Non-Equilibrium Molecules. CoRR abs/2011.14115 (2020) - 2019
- [c81]Johannes Klicpera, Aleksandar Bojchevski, Stephan Günnemann:
Predict then Propagate: Graph Neural Networks meet Personalized PageRank. ICLR (Poster) 2019 - [c73]Johannes Klicpera, Stefan Weißenberger, Stephan Günnemann:
Diffusion Improves Graph Learning. NeurIPS 2019: 13333-13345 - [i20]Johannes Klicpera, Stefan Weißenberger, Stephan Günnemann:
Diffusion Improves Graph Learning. CoRR abs/1911.05485 (2019) - 2018
- [i12]Johannes Klicpera, Aleksandar Bojchevski, Stephan Günnemann:
Personalized Embedding Propagation: Combining Neural Networks on Graphs with Personalized PageRank. CoRR abs/1810.05997 (2018)
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