Emre Kavak — accepted AI-conference papers

2026

DISCO: Mitigating Bias in Deep Learning with Conditional Distance Correlation

Emre Kavak, Tom Nuno Wolf, Christian Wachinger

ICML 2026oral

Dataset bias often leads deep learning models to exploit spurious correlations instead of task-relevant signals. We introduce the Standard Anti-Causal Model (SAM), a unifying causal framework that characterizes bias mechanisms and yields a conditional independence criterion for causal stability. Bui…

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2025

SIC: Similarity-Based Interpretable Image Classification with Neural Networks

Tom Nuno Wolf, Emre Kavak, Fabian Bongratz, Christian Wachinger

ICCV 2025poster

The deployment of deep learning models in critical domains necessitates a balance between high accuracy and interpretability.We introduce SIC, an inherently interpretable neural network that provides local and global explanations of its decision-making process.Leveraging the concept of case-based re…

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