CV

Education

• Ph.D in Machine Learning, University of Mannheim, 05/2025 (expected)
  • Focus: Machine Learning, Tabular Data, Tree-Based Models, Explainable AI
• M.S. in Business Informatics (Data Science Track), University of Mannheim, 2019
• B.S. in Business Informatics, University of Mannheim, 2017

Work experience

• 2019-now: Scientific Researcher and PhD Candidate
  • University of Mannheim
  • Topics: Deep Learning for Tabular Data, Tree Ensemble Methods, Explainable AI
• 10/2024 - 03/2025: Adjunct Lecturer
  • Technical University of Clausthal
  • Lecture: “Grundlagen der Künstlichen Intelligenz” (Introduction to AI)

Skills

• Technical Skills
  • Deep Learning (TensorFlow, PyTorch, JAX)
  • Predictive Modeling
  • Computer Vision
  • Reinforcement Learning
  • Time Series Forecasting
• Programming
  • Python
  • R
  • Java
  • C/C++
• Languages
  • German (native)
  • English (Fluent)
  • Italian (Conversational)

Publications

Mitigating Information Loss in Tree-Based Reinforcement Learning via Direct Optimization

Marton, Sascha, et al. (2025). "Mitigating Information Loss in Tree-Based Reinforcement Learning via Direct Optimization." The Thirteenth International Conference on Learning Representations. 1(1).

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory

Marton, Sascha, et al. (2025). "Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory." New Frontiers in Associative Memory workshop at ICLR 2025. 1(1).

GRANDE: Gradient-Based Decision Tree Ensembles for Tabular Data

Marton, Sascha, et al. (2024). "GRANDE: Gradient-Based Decision Tree Ensembles for Tabular Data." The Twelfth International Conference on Learning Representations. 1(1).

GradTree: Learning Axis-Aligned Decision Trees with Gradient Descent

Marton, Sascha, et al. (2024). "GRANDE: Gradient-Based Decision Tree Ensembles for Tabular Data." Proceedings of the AAAI Conference on Artificial Intelligence. 38(13).

Explaining neural networks without access to training data

Marton, Sascha, et al. (2024). "Explaining neural networks without access to training data." Machine Learning. 113(6).

Talks

GRANDE: Gradient-Based Decision Tree Ensembles for Tabular Data

May 08, 2024

Talk at Messe Wien Exhibition und Congress Center, Vienna, Austria

GradTree: Learning Axis-Aligned Decision Trees with Gradient Descent

February 22, 2024

Talk at Vancouver Convention Centre, Vancouver, Canada

Explaining neural networks without access to training data

November 14, 2023

Talk at Acıbadem University Conference Center, Istanbul, Turkey