Understanding Patch-Based Learning by Explaining Predictions. - Christopher J. Anders; Grégoire Montavon; Wojciech Samek; Klaus-Robert Müller (CoRR, 2018)

Explanations can be manipulated and geometry is to blame. - Ann-Kathrin Dombrowski; Maximilian Alber; Christopher J. Anders; Marcel Ackermann 001; Klaus-Robert Müller; Pan Kessel (NeurIPS, 2019)

Analyzing ImageNet with Spectral Relevance Analysis: Towards ImageNet un-Hans'ed. - Christopher J. Anders; Talmaj Marinc; David Neumann; Wojciech Samek; Klaus-Robert Müller; Sebastian Lapuschkin (CoRR, 2019)

Understanding Patch-Based Learning of Video Data by Explaining Predictions. - Christopher J. Anders; Grégoire Montavon; Wojciech Samek; Klaus-Robert Müller (Explainable AI, 2019)

Fairwashing explanations with off-manifold detergent. - Christopher J. Anders; Plamen Pasliev; Ann-Kathrin Dombrowski; Klaus-Robert Müller; Pan Kessel (ICML, 2020)

Toward Interpretable Machine Learning: Transparent Deep Neural Networks and Beyond. - Wojciech Samek; Grégoire Montavon; Sebastian Lapuschkin; Christopher J. Anders; Klaus-Robert Müller (CoRR, 2020)

On Estimation of Thermodynamic Observables in Lattice Field Theories with Deep Generative Models. - Kim A. Nicoli; Christopher J. Anders; Lena Funcke; Tobias Hartung; Karl Jansen; Pan Kessel; Shinichi Nakajima; Paolo Stornati (CoRR, 2020)

Software for Dataset-wide XAI: From Local Explanations to Global Insights with Zennit, CoRelAy, and ViRelAy. - Christopher J. Anders; David Neumann; Wojciech Samek; Klaus-Robert Müller; Sebastian Lapuschkin (CoRR, 2021)

Machine Learning of Thermodynamic Observables in the Presence of Mode Collapse. - Kim A. Nicoli; Christopher J. Anders; Lena Funcke; Tobias Hartung; Karl Jansen; Pan Kessel; Shinichi Nakajima; Paolo Stornati (CoRR, 2021)

Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications. - Wojciech Samek; Grégoire Montavon; Sebastian Lapuschkin; Christopher J. Anders; Klaus-Robert Müller (Proc. IEEE, 2021)

PatClArC: Using Pattern Concept Activation Vectors for Noise-Robust Model Debugging. - Frederik Pahde; Leander Weber; Christopher J. Anders; Wojciech Samek; Sebastian Lapuschkin (CoRR, 2022)

Finding and removing Clever Hans: Using explanation methods to debug and improve deep models. - Christopher J. Anders; Leander Weber; David Neumann; Wojciech Samek; Klaus-Robert Müller; Sebastian Lapuschkin (Inf. Fusion, 2022)

Towards robust explanations for deep neural networks. - Ann-Kathrin Dombrowski; Christopher J. Anders; Klaus-Robert Müller; Pan Kessel (Pattern Recognit., 2022)

Towards Fixing Clever-Hans Predictors with Counterfactual Knowledge Distillation. - Sidney Bender; Christopher J. Anders; Pattarawat Chormai; Heike Marxfeld; Jan Herrmann; Grégoire Montavon (ICCV (Workshops), 2023)

Physics-Informed Bayesian Optimization of Variational Quantum Circuits. - Kim Nicoli; Christopher J. Anders; Lena Funcke; Tobias Hartung; Karl Jansen; Stefan Kühn; Klaus-Robert Müller; Paolo Stornati; Pan Kessel; Shinichi Nakajima (NeurIPS, 2023)

Detecting and Mitigating Mode-Collapse for Flow-based Sampling of Lattice Field Theories. - Kim A. Nicoli; Christopher J. Anders; Tobias Hartung; Karl Jansen; Pan Kessel; Shinichi Nakajima (CoRR, 2023)

From Hope to Safety: Unlearning Biases of Deep Models by Enforcing the Right Reasons in Latent Space. - Maximilian Dreyer; Frederik Pahde; Christopher J. Anders; Wojciech Samek; Sebastian Lapuschkin (CoRR, 2023)

From Hope to Safety: Unlearning Biases of Deep Models via Gradient Penalization in Latent Space. - Maximilian Dreyer; Frederik Pahde; Christopher J. Anders; Wojciech Samek; Sebastian Lapuschkin (AAAI, 2024)

Adaptive Observation Cost Control for Variational Quantum Eigensolvers. - Christopher J. Anders; Kim Andrea Nicoli; Bingting Wu; Naima Elosegui; Samuele Pedrielli; Lena Funcke; Karl Jansen; Stefan Kühn; Shinichi Nakajima (ICML, 2024)

Debugging learning algorithms: understanding and correcting machine learning models. - Christopher J. Anders (2024)

Navigating Neural Space: Revisiting Concept Activation Vectors to Overcome Directional Divergence. - Frederik Pahde; Maximilian Dreyer; Moritz Weckbecker; Leander Weber; Christopher J. Anders; Thomas Wiegand 001; Wojciech Samek; Sebastian Lapuschkin (ICLR, 2025)

Bayesian Parameter Shift Rule in Variational Quantum Eigensolvers. - Samuele Pedrielli; Christopher J. Anders; Lena Funcke; Karl Jansen; Kim A. Nicoli; Shinichi Nakajima (CoRR, 2025)