← Authors

Simon Geisler

16 papers · 2020–2025 · 4 conferences · across top CS/AI conferences

Achievements

🗺️ Taxonomy Completionist (18) 🌉 Interdisciplinary Bridge 🐝 Cross-Pollinator (15) 🐣 Hot Topic Early Bird 🧭 Keyword Pioneer 🌍 Conference Polyglot (4) 🏃 Academic Marathon (5) 🤝 Dynamic Duo (16) 👑 Triple Crown 🏆 Keyword Champion (2) ❓ The Questioner 💎 Century Club (16) ⚡ Prolific Year (5) 🔥 Unstoppable (6)

Conferences

NIPS (7) ICLR (4) ICML (4) CORL (1)

Top co-authors

Stephan Günnemann (16) Daniel Zügner (6) Aleksandar Bojchevski (4) Bertrand Charpentier (4) Daniel Sturm (2) Lukas Gosch (2) Tom Wollschläger (2) Vincent Cohen-Addad (2) Jan Schuchardt (2) Johannes Gasteiger (2)

Keywords

graph neural network (8) message passing (3) node classification (2) robust aggregation (2) adversarial robustness (2) adversarial attack (2) positional encoding (2) robust statistics (1) network pruning (1) adversarial training (1) robot learning (1) weisfeiler-lehman test (1) directed graph (1) bayesian posterior (1) spectral method (1) randomized smoothing (1) adversarial defense (1) normalizing flow (1) gradient flow (1) out-of-distribution detection (1)

Papers

REINFORCE Adversarial Attacks on Large Language Models: An Adaptive, Distributional, and Semantic Objective ICML 2025
The Geometry of Refusal in Large Language Models: Concept Cones and Representational Independence ICML 2025
Graph Neural Networks for Edge Signals: Orientation Equivariance and Invariance ICLR 2025
Spatio-Spectral Graph Neural Networks NIPS 2024
Topology-Matching Normalizing Flows for Out-of-Distribution Detection in Robot Learning CORL 2023
Revisiting Robustness in Graph Machine Learning ICLR 2023
Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions NIPS 2023
Transformers Meet Directed Graphs ICML 2023
Generalization of Neural Combinatorial Solvers Through the Lens of Adversarial Robustness ICLR 2022
Are Defenses for Graph Neural Networks Robust? NIPS 2022
Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural Networks NIPS 2022
Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions ICLR 2022
Winning the Lottery Ahead of Time: Efficient Early Network Pruning ICML 2022
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification NIPS 2021
Robustness of Graph Neural Networks at Scale NIPS 2021
Reliable Graph Neural Networks via Robust Aggregation NIPS 2020