See the rest of our team here.
Our research focuses on machine learning on graphs, non-stationary and evolving environments, and dynamical systems. Applications cover neuroscience, power grids, chemistry, dynamical systems, among many others.
See the complete list of our publications here:
Our group is active in open source software development and we maintain several Python libraries based on our research.
A library for building graph neural networks in Keras and Tensorflow.
A Python library for detecting changes in stationarity in sequences of graphs.
A Keras library that provides multiple deep architectures for multi-step time-series forecasting.
The development of Spektral and CDG was supported by project ALPSFORT (200021 172671) of the Swiss National Science Foundation.