Sascha Marton

25 papers A* 5A 2Journal 14Unranked 3
YearRankTypeTitle / Venue / Authors
2026 J jnl
Learning Tree-Based Models with Gradient Descent.
CoRR
Sascha Marton
2025 A conf
Beyond Pixels: Enhancing LIME with Hierarchical Features and Segmentation Foundation Models.
ECAI
Patrick Knab, Sascha Marton, Christian Bartelt
2025 J jnl
Concepts in Motion: Temporal Bottlenecks for Interpretable Video Classification.
CoRR
Patrick Knab, Sascha Marton, Philipp J. Schubert, Drago Guggiana, Christian Bartelt
2025 A* conf
DCBM: Data-Efficient Visual Concept Bottleneck Models.
ICML
Katharina Prasse, Patrick Knab, Sascha Marton, Christian Bartelt, Margret Keuper
2025 J jnl
Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory.
CoRR
Sascha Marton, Moritz Schneider
2025 A conf
Disentangling Exploration of Large Language Models by Optimal Exploitation.
ECAI
Tim Grams, Patrick Betz, Sascha Marton, Stefan Lüdtke, Christian Bartelt
2025 — —
Learning tree-based models with gradient descent.
Sascha Marton
2025 A* conf
Mitigating Information Loss in Tree-Based Reinforcement Learning via Direct Optimization.
ICLR
Sascha Marton, Tim Grams, Florian Vogt, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt
2025 — conf
Which LIME Should I Trust? Concepts, Challenges, and Solutions.
xAI (2)
Patrick Knab, Sascha Marton, Udo Schlegel, Christian Bartelt
2025 J jnl
Which LIME should I trust? Concepts, Challenges, and Solutions.
CoRR
Patrick Knab, Sascha Marton, Udo Schlegel, Christian Bartelt
2024 A* conf
A Data-Centric Perspective on Evaluating Machine Learning Models for Tabular Data.
NeurIPS
Andrej Tschalzev, Sascha Marton, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt
2024 J jnl
A Data-Centric Perspective on Evaluating Machine Learning Models for Tabular Data.
CoRR
Andrej Tschalzev, Sascha Marton, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt
2024 J jnl
Aligning Visual and Semantic Interpretability through Visually Grounded Concept Bottleneck Models.
CoRR
Patrick Knab, Katharina Prasse, Sascha Marton, Christian Bartelt, Margret Keuper
2024 J jnl
DSEG-LIME - Improving Image Explanation by Hierarchical Data-Driven Segmentation.
CoRR
Patrick Knab, Sascha Marton, Christian Bartelt
2024 J jnl
Explaining neural networks without access to training data.
Mach. Learn.
Sascha Marton, Stefan Lüdtke, Christian Bartelt, Andrej Tschalzev, Heiner Stuckenschmidt
2024 A* conf
GRANDE: Gradient-Based Decision Tree Ensembles for Tabular Data.
ICLR
Sascha Marton, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt
2024 A* conf
GradTree: Learning Axis-Aligned Decision Trees with Gradient Descent.
AAAI
Sascha Marton, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt
2024 — conf
Interpreting Outliers in Time Series Data through Decoding Autoencoder.
TempXAI@PKDD/ECML
Patrick Knab, Sascha Marton, Christian Bartelt, Robert Fuder
2024 J jnl
Interpreting Outliers in Time Series Data through Decoding Autoencoder.
CoRR
Patrick Knab, Sascha Marton, Christian Bartelt, Robert Fuder
2024 J jnl
SYMPOL: Symbolic Tree-Based On-Policy Reinforcement Learning.
CoRR
Sascha Marton, Tim Grams, Florian Vogt, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt
2023 — conf
Bias Mitigation for Large Language Models using Adversarial Learning.
AEQUITAS@ECAI
Jasmina S. Ernst, Sascha Marton, Jannik Brinkmann, Eduardo Vellasques, Damien Foucard, Martin Kraemer, Marian Lambert
2023 J jnl
GRANDE: Gradient-Based Decision Tree Ensembles.
CoRR
Sascha Marton, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt
2023 J jnl
Learning Decision Trees with Gradient Descent.
CoRR
Sascha Marton, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt
2022 J jnl
Explaining Neural Networks without Access to Training Data.
CoRR
Sascha Marton, Stefan Lüdtke, Christian Bartelt, Andrej Tschalzev, Heiner Stuckenschmidt
2020 J jnl
xRAI: Explainable Representations through AI.
CoRR
Christian Bartelt, Sascha Marton, Heiner Stuckenschmidt