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← Authors

Daniel Zügner

14 papers · 2018–2024 · 4 conferences · across top CS/AI conferences

Achievements

Jump to papers ↓
+7 more ↓ 🏃 Academic Marathon (6) 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (4) 🧭 Keyword Pioneer 🐝 Cross-Pollinator (13)
🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 👑 Triple Crown 🤝 Dynamic Duo (14) ❓ The Questioner 💎 Century Club (14) 🔥 Unstoppable (7)

Conferences

NIPS (6) ICLR (4) ICML (3) IJCAI (1)

Top co-authors

Stephan Günnemann (14) Bertrand Charpentier (8) Simon Geisler (6) Aleksandar Bojchevski (2) Morgane Ayle (2) Daniel Sturm (1) Tobias Kirschstein (1) Sandhya Giri (1) Lukas Gosch (1) Oliver Borchert (1)

Keywords

graph neural network (6) node classification (3) uncertainty estimation (2) adversarial attack (2) robust aggregation (2) adversarial robustness (2) out-of-distribution detection (2) bayesian learning (1) robust statistics (1) lottery ticket hypothesis (1) epistemic uncertainty (1) graph generation (1) network pruning (1) hierarchical clustering (1) uncertainty quantification (1) semi-supervised learning (1) random walk (1) message passing (1) bayesian posterior (1) label propagation (1)

Papers

Expected Probabilistic Hierarchies NIPS 2024 Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions NIPS 2023 End-to-End Learning of Probabilistic Hierarchies on Graphs ICLR 2022 Winning the Lottery Ahead of Time: Efficient Early Network Pruning ICML 2022 Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions ICLR 2022 Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable? ICML 2021 Language-Agnostic Representation Learning of Source Code from Structure and Context ICLR 2021 Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification NIPS 2021 Robustness of Graph Neural Networks at Scale NIPS 2021 Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts NIPS 2020 Reliable Graph Neural Networks via Robust Aggregation NIPS 2020 Adversarial Attacks on Graph Neural Networks via Meta Learning ICLR 2019 Adversarial Attacks on Neural Networks for Graph Data IJCAI 2019 NetGAN: Generating Graphs via Random Walks ICML 2018