Ping Xiong
Ping Xiong
Doctoral Researcher
Affiliation: BIFOLD
- M.Sc. Industrial Engineering, TU Berlin
- B.Sc. Industrial Engineering, TU Berlin
- Member of BIFOLD Graduate School
- Explainable AI
- Graph Neural Network
- Bayesian Learning Applications
Ping Xiong, Thomas Schnake, Grégoire Montavon, Klaus-Robert Müller, Shinichi Nakajima
Normalized Relevance Measure as a Unifying Framework to Explain Neural Network Latent Structures
Haci Ismail Aslan, Philipp Wiesner, Ping Xiong, Odej Kao
β-GNN: A Robust Ensemble Approach Against Graph Structure Perturbation
Haci Ismail Aslan, Philipp Wiesner, Ping Xiong, Odej Kao
-GNN: A Robust Ensemble Approach Against Graph Structure Perturbation
Thomas Schnake, Farnoush Rezaei Jafaria, Jonas Lederer, Ping Xiong, Shinichi Nakajima, Stefan Gugler, Grégoire Montavon, Klaus-Robert Müller
Towards Symbolic XAI -- Explanation Through Human Understandable Logical Relationships Between Features
Ping Xiong, Thomas Schnake, Michael Gastegger, Grégoire Montavon, Klaus Robert Müller, Shinichi Nakajima
Relevant Walk Search for Explaining Graph Neural Networks
Symbolic XAI
Researchers at BIFOLD have been exploring how to make AI explain itself in the same way, people explain themselves. The team’s work focuses on making AI predictions as clear and intuitive as a human explanation.