Gasteiger, Johannes

16 publications

ICML 2025 REINFORCE Adversarial Attacks on Large Language Models: An Adaptive, Distributional, and Semantic Objective Simon Geisler, Tom Wollschläger, M. H. I. Abdalla, Vincent Cohen-Addad, Johannes Gasteiger, Stephan Günnemann

ICML 2025 The Geometry of Refusal in Large Language Models: Concept Cones and Representational Independence Tom Wollschläger, Jannes Elstner, Simon Geisler, Vincent Cohen-Addad, Stephan Günnemann, Johannes Gasteiger

ICMLW 2024 Attacking Large Language Models with Projected Gradient Descent Simon Geisler, Tom Wollschläger, M. H. I. Abdalla, Johannes Gasteiger, Stephan Günnemann

NeurIPS 2023 Accelerating Molecular Graph Neural Networks via Knowledge Distillation Filip Ekström Kelvinius, Dimitar Georgiev, Artur Toshev, Johannes Gasteiger

ICMLW 2023 Accelerating Molecular Graph Neural Networks via Knowledge Distillation Filip Ekström Kelvinius, Dimitar Georgiev, Artur Toshev, Johannes Gasteiger

ICML 2023 Ewald-Based Long-Range Message Passing for Molecular Graphs Arthur Kosmala, Johannes Gasteiger, Nicholas Gao, Stephan Günnemann

UAI 2023 SubMix: Learning to Mix Graph Sampling Heuristics Sami Abu-El-Haija, Joshua V. Dillon, Bahare Fatemi, Kyriakos Axiotis, Neslihan Bulut, Johannes Gasteiger, Bryan Perozzi, Mohammadhossein Bateni

TMLR 2022 GemNet-OC: Developing Graph Neural Networks for Large and Diverse Molecular Simulation Datasets Johannes Gasteiger, Muhammed Shuaibi, Anuroop Sriram, Stephan Günnemann, Zachary Ward Ulissi, C. Lawrence Zitnick, Abhishek Das

LoG 2022 Influence-Based Mini-Batching for Graph Neural Networks Johannes Gasteiger, Chendi Qian, Stephan Günnemann

ICLR 2021 Collective Robustness Certificates: Exploiting Interdependence in Graph Neural Networks Jan Schuchardt, Aleksandar Bojchevski, Johannes Gasteiger, Stephan Günnemann

NeurIPS 2021 Directional Message Passing on Molecular Graphs via Synthetic Coordinates Johannes Gasteiger, Chandan Yeshwanth, Stephan Günnemann

NeurIPS 2021 GemNet: Universal Directional Graph Neural Networks for Molecules Johannes Gasteiger, Florian Becker, Stephan Günnemann

ICML 2021 Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, and More Johannes Gasteiger, Marten Lienen, Stephan Günnemann

ICML 2020 Efficient Robustness Certificates for Discrete Data: Sparsity-Aware Randomized Smoothing for Graphs, Images and More Aleksandar Bojchevski, Johannes Gasteiger, Stephan Günnemann

NeurIPS 2019 Diffusion Improves Graph Learning Johannes Gasteiger, Stefan Weißenberger, Stephan Günnemann

ICLR 2019 Predict Then Propagate: Graph Neural Networks Meet Personalized PageRank Johannes Gasteiger, Aleksandar Bojchevski, Stephan Günnemann