Daniel Zügner
14 papers · 2018–2024 · 4 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (30) 🏃 Academic Marathon · Sprint 🌍 Conference Polyglot · Bronze 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird
👑
Triple Crown
🤝
Dynamic Duo
(14)
🏆
Keyword Champion
📈
Trend Setter
❓
The Questioner
🔥
Unstoppable · Bronze
🗃️
Keyword Collector
(61)
💎
Century Club · Bronze
Venues
Top co-authors
Research topics
Machine Learning
(11)
Deep Learning
(10)
Architectures
(7)
Optimization & Theory
(7)
Artificial Intelligence
(6)
Learning Types
(6)
Core AI
(4)
Core Methods
(4)
Bayesian & Probabilistic
(3)
Application Areas
(2)
Models
(2)
Computer Science
(1)
Data Science & Analytics
(1)
Applications · Data Science & Analytics
(1)
Applications · Computer Science
(1)
Keywords
graph neural network
(8)
node classification
(4)
adversarial attack
(3)
out-of-distribution detection
(3)
link prediction
(2)
uncertainty estimation
(2)
hierarchical clustering
(2)
adversarial robustness
(2)
robust aggregation
(2)
probabilistic model
(2)
normalizing flow
(2)
epistemic uncertainty
(1)
semi-supervised learning
(1)
robust statistics
(1)
uncertainty quantification
(1)
label propagation
(1)
unsupervised learning
(1)
graph clustering
(1)
posterior distribution
(1)
bayesian inference
(1)
Papers
Expected Probabilistic Hierarchies
NeurIPS 2024
Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions
NeurIPS 2023
End-to-End Learning of Probabilistic Hierarchies on Graphs
ICLR 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
Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable?
ICML 2021
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification
NeurIPS 2021
Language-Agnostic Representation Learning of Source Code from Structure and Context
ICLR 2021
Robustness of Graph Neural Networks at Scale
NeurIPS 2021
Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts
NeurIPS 2020
Reliable Graph Neural Networks via Robust Aggregation
NeurIPS 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