Manuel Welte

Manuel Welte is a Researcher at BIFOLD (Berlin Institute for the Foundations of Learning and Data) and a PhD candidate at the Technical University of Berlin. His work focuses on transforming neural network architectures into inherently interpretable machine learning models.

• Education: M.Sc. in Computer Science from Freie Universität Berlin (2024).

Research Interests:

• Explainable Machine Learning
• Inherently Interpretable Models
• ML for Medical Applications
• Probabilistic ML