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Sascha Marton
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2020 – today
- 2024
- [j1]Sascha Marton, Stefan Lüdtke, Christian Bartelt, Andrej Tschalzev, Heiner Stuckenschmidt:
Explaining neural networks without access to training data. Mach. Learn. 113(6): 3633-3652 (2024) - [c4]Sascha Marton, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt:
GradTree: Learning Axis-Aligned Decision Trees with Gradient Descent. AAAI 2024: 14323-14331 - [c3]Sascha Marton, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt:
GRANDE: Gradient-Based Decision Tree Ensembles for Tabular Data. ICLR 2024 - [c2]Patrick Knab, Sascha Marton, Christian Bartelt, Robert Fuder:
Interpreting Outliers in Time Series Data through Decoding Autoencoder. TempXAI@PKDD/ECML 2024: 44-57 - [i8]Patrick Knab, Sascha Marton, Christian Bartelt:
DSEG-LIME - Improving Image Explanation by Hierarchical Data-Driven Segmentation. CoRR abs/2403.07733 (2024) - [i7]Andrej Tschalzev, Sascha Marton, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt:
A Data-Centric Perspective on Evaluating Machine Learning Models for Tabular Data. CoRR abs/2407.02112 (2024) - [i6]Sascha Marton, Tim Grams, Florian Vogt, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt:
SYMPOL: Symbolic Tree-Based On-Policy Reinforcement Learning. CoRR abs/2408.08761 (2024) - [i5]Patrick Knab, Sascha Marton, Christian Bartelt, Robert Fuder:
Interpreting Outliers in Time Series Data through Decoding Autoencoder. CoRR abs/2409.01713 (2024) - 2023
- [c1]Jasmina S. Ernst, Sascha Marton, Jannik Brinkmann, Eduardo Vellasques, Damien Foucard, Martin Kraemer, Marian Lambert:
Bias Mitigation for Large Language Models using Adversarial Learning. AEQUITAS@ECAI 2023 - [i4]Sascha Marton, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt:
Learning Decision Trees with Gradient Descent. CoRR abs/2305.03515 (2023) - [i3]Sascha Marton, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt:
GRANDE: Gradient-Based Decision Tree Ensembles. CoRR abs/2309.17130 (2023) - 2022
- [i2]Sascha Marton, Stefan Lüdtke, Christian Bartelt, Andrej Tschalzev, Heiner Stuckenschmidt:
Explaining Neural Networks without Access to Training Data. CoRR abs/2206.04891 (2022) - 2020
- [i1]Christian Bartelt, Sascha Marton, Heiner Stuckenschmidt:
xRAI: Explainable Representations through AI. CoRR abs/2012.06006 (2020)
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