Daniel Zügner

1. MatterGen: a generative model for inorganic materials design
   2023/12/06 by Claudio Zeni, Zeni, Claudio, Robert Pinsler +41 · 1 voice · 25 citations
   Computer Science · Engineering · Materials Science · Physics and Astronomy · #Machine Learning in Materials Science #Modular Robots and Swarm Intelligence #cond-mat.mtrl-sci #cs.AI
2. MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
   2024/05/08 by Han Yang, Chenxi Hu, Yang, Han +44 · 1 voice · 81 citations
   Materials Science · Physics and Astronomy · #Machine Learning in Materials Science #Nuclear Physics and Applications #cond-mat.mtrl-sci
3. Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts
   2020/06/16 by Bertrand Charpentier, Daniel Zügner, Charpentier, Bertrand +3 · 23 citations
   Computer Science · #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML)
4. Robustness of Graph Neural Networks at Scale
   2021/10/26 by Simon Geisler, Tobias S. Schmidt, Geisler, Simon +9 · 16 citations
   Computer Science · Materials Science · #Adversarial Robustness in Machine Learning #Advanced Graph Neural Networks #Machine Learning in Materials Science
5. Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification
   2021/10/26 by Maximilian Stadler, Stadler, Maximilian, Bertrand Charpentier +7 · 9 citations
   Computer Science · #Advanced Graph Neural Networks #Adversarial Robustness in Machine Learning #Bayesian Modeling and Causal Inference #Computational Drug Discovery Methods #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
6. Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions
   2023/06/27 by Lukas Gosch, Gosch, Lukas, Simon Geisler +9 · 8 citations
   Computer Science · #Advanced Graph Neural Networks #Adversarial Robustness in Machine Learning #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
7. Natural Posterior Network: Deep Bayesian Uncertainty for Exponential Family Distributions
   2021/05/10 by Bertrand Charpentier, Charpentier, Bertrand, Oliver Borchert +7 · 3 citations
   Computer Science · #Anomaly Detection Techniques and Applications #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
8. Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable?
   2020/10/28 by Anna-Kathrin Kopetzki, Kopetzki, Anna-Kathrin, Bertrand Charpentier +7 · 3 citations
   Computer Science · Biochemistry, Genetics and Molecular Biology · #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #Bacillus and Francisella bacterial research
9. Probing the Limit of Heat Transfer in Inorganic Crystals with Deep Learning
   2025/03/14 by Zekun Chen, Li, Jielan, Chen, Zekun +42 · 4 citations
   Materials Science · #Advanced Thermoelectric Materials and Devices #FOS: Physical sciences #Machine Learning in Materials Science #Materials Science (cond-mat.mtrl-sci) #Thermal properties of materials
10. Winning the Lottery Ahead of Time: Efficient Early Network Pruning
    2022/06/21 by John Rachwan, Rachwan, John, Daniel Zügner +9 · 1 citation
    Computer Science · #Advanced Neural Network Applications #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #FOS: Computer and information sciences #Machine Learning (cs.LG)
11. MatterSim-MT: A multi-task foundation model for in silico materials characterization
    2026/05/08 by Han Yang, Xixian Liu, Chenxi Hu +25 · 1 voice
    Physics and Astronomy · #cond-mat.mtrl-sci