Sascha Marton

According to our database, Sascha Marton authored at least 22 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of five.

2026

Revisiting Metafeatures to Explain Model Differences on Tabular Data.

Markus Herre, Andrej Tschalzev, Sascha Marton, Christian Bartelt

CoRR, May, 2026

Learning Tree-Based Models with Gradient Descent.

Sascha Marton

CoRR, March, 2026

2025

Concepts in Motion: Temporal Bottlenecks for Interpretable Video Classification.

Patrick Knab, Sascha Marton, Philipp J. Schubert, Drago Guggiana, Christian Bartelt

CoRR, September, 2025

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

Sascha Marton, Moritz Schneider

CoRR, February, 2025

Learning tree-based models with gradient descent.

Sascha Marton

PhD thesis, 2025

Which LIME Should I Trust? Concepts, Challenges, and Solutions.

Patrick Knab, Sascha Marton, Udo Schlegel, Christian Bartelt

Proceedings of the Explainable Artificial Intelligence, 2025

DCBM: Data-Efficient Visual Concept Bottleneck Models.

Katharina Prasse, Patrick Knab, Sascha Marton, Christian Bartelt, Margret Keuper

Proceedings of the Forty-second International Conference on Machine Learning, 2025

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

Sascha Marton, Tim Grams, Florian Vogt, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Beyond Pixels: Enhancing LIME with Hierarchical Features and Segmentation Foundation Models.

Patrick Knab, Sascha Marton, Christian Bartelt

Proceedings of the ECAI 2025 - 28th European Conference on Artificial Intelligence, 25-30 October 2025, Bologna, Italy, 2025

Disentangling Exploration of Large Language Models by Optimal Exploitation.

Tim Grams, Patrick Betz, Sascha Marton, Stefan Lüdtke, Christian Bartelt

Proceedings of the ECAI 2025 - 28th European Conference on Artificial Intelligence, 25-30 October 2025, Bologna, Italy, 2025

2024

Explaining neural networks without access to training data.

Sascha Marton, Stefan Lüdtke, Christian Bartelt, Andrej Tschalzev, Heiner Stuckenschmidt

Mach. Learn., June, 2024

Aligning Visual and Semantic Interpretability through Visually Grounded Concept Bottleneck Models.

Patrick Knab, Katharina Prasse, Sascha Marton, Christian Bartelt, Margret Keuper

CoRR, 2024

SYMPOL: Symbolic Tree-Based On-Policy Reinforcement Learning.

Sascha Marton, Tim Grams, Florian Vogt, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt

CoRR, 2024

DSEG-LIME - Improving Image Explanation by Hierarchical Data-Driven Segmentation.

Patrick Knab, Sascha Marton, Christian Bartelt

CoRR, 2024

Interpreting Outliers in Time Series Data through Decoding Autoencoder.

Patrick Knab, Sascha Marton, Christian Bartelt, Robert Fuder

Proceedings of the Workshop on Explainable AI for Time Series and Data Streams (TempXAI 2024) co-located with The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2024), 2024

A Data-Centric Perspective on Evaluating Machine Learning Models for Tabular Data.

Andrej Tschalzev, Sascha Marton, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

GRANDE: Gradient-Based Decision Tree Ensembles for Tabular Data.

Sascha Marton, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt

Proceedings of the Twelfth International Conference on Learning Representations, 2024

GradTree: Learning Axis-Aligned Decision Trees with Gradient Descent.

Sascha Marton, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

GRANDE: Gradient-Based Decision Tree Ensembles.

Sascha Marton, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt

CoRR, 2023

Learning Decision Trees with Gradient Descent.

Sascha Marton, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt

CoRR, 2023

Bias Mitigation for Large Language Models using Adversarial Learning.

Jasmina S. Ernst, Sascha Marton, Jannik Brinkmann, Eduardo Vellasques, Damien Foucard, Martin Kraemer, Marian Lambert

Proceedings of the 1st Workshop on Fairness and Bias in AI co-located with 26th European Conference on Artificial Intelligence (ECAI 2023), 2023

2020

xRAI: Explainable Representations through AI.

Christian Bartelt, Sascha Marton, Heiner Stuckenschmidt

CoRR, 2020