1k citations · 1.9k across the 12 of their papers we have counts for
13 papers
MatterGen: a generative model for inorganic materials design
Claudio Zeni, Robert Pinsler, Daniel Zügner +18
The design of functional materials with desired properties is essential in driving technological advances in areas like energy storage, catalysis, and carbon capture. Generative mo…
Training Differentially Private Graph Neural Networks with Random Walk Sampling
Morgane Ayle, Jan Schuchardt, Lukas Gosch +2
Deep learning models are known to put the privacy of their training data at risk, which poses challenges for their safe and ethical release to the public. Differentially private st…
Monte Carlo EM for Deep Time Series Anomaly Detection
François-Xavier Aubet, Daniel Zügner, Jan Gasthaus
Time series data are often corrupted by outliers or other kinds of anomalies. Identifying the anomalous points can be a goal on its own (anomaly detection), or a means to improving…
A Study of Joint Graph Inference and Forecasting
Daniel Zügner, François-Xavier Aubet, Victor Garcia Satorras +3
We study a recent class of models which uses graph neural networks (GNNs) to improve forecasting in multivariate time series. The core assumption behind these models is that there…
On Out-of-distribution Detection with Energy-based Models
Sven Elflein, Bertrand Charpentier, Daniel Zügner +1
Several density estimation methods have shown to fail to detect out-of-distribution (OOD) samples by assigning higher likelihoods to anomalous data. Energy-based models (EBMs) are…
Reliable Graph Neural Networks via Robust Aggregation
Simon Geisler, Daniel Zügner, Stephan Günnemann
Perturbations targeting the graph structure have proven to be extremely effective in reducing the performance of Graph Neural Networks (GNNs), and traditional defenses such as adve…