Christopher J. Anders

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 22

Top Topics

Discriminative Methods

Generating Explanations

Manifold Embedding

Top Venues

Pattern Recognit.

Publications

Maximilian Dreyer, Frederik Pahde, Christopher J. Anders, Wojciech Samek, Sebastian Lapuschkin
From Hope to Safety: Unlearning Biases of Deep Models via Gradient Penalization in Latent Space. AAAI (2024)
Kim A. Nicoli, Christopher J. Anders, Lena Funcke, Tobias Hartung, Karl Jansen, Stefan Kühn, Klaus-Robert Müller, Paolo Stornati, Pan Kessel, Shinichi Nakajima
Physics-Informed Bayesian Optimization of Variational Quantum Circuits. CoRR (2024)
Maximilian Dreyer, Frederik Pahde, Christopher J. Anders, Wojciech Samek, Sebastian Lapuschkin
From Hope to Safety: Unlearning Biases of Deep Models by Enforcing the Right Reasons in Latent Space. CoRR (2023)
Kim A. Nicoli, Christopher J. Anders, Tobias Hartung, Karl Jansen, Pan Kessel, Shinichi Nakajima
Detecting and Mitigating Mode-Collapse for Flow-based Sampling of Lattice Field Theories. CoRR (2023)
Sidney Bender, Christopher J. Anders, Pattarawat Chormai, Heike Marxfeld, Jan Herrmann, Grégoire Montavon
Towards Fixing Clever-Hans Predictors with Counterfactual Knowledge Distillation. ICCV (Workshops) (2023)
Sidney Bender, Christopher J. Anders, Pattarawat Chormai, Heike Marxfeld, Jan Herrmann, Grégoire Montavon
Towards Fixing Clever-Hans Predictors with Counterfactual Knowledge Distillation. CoRR (2023)
Kim Nicoli, Christopher J. Anders, Lena Funcke, Tobias Hartung, Karl Jansen, Stefan Kühn, Klaus-Robert Müller, Paolo Stornati, Pan Kessel, Shinichi Nakajima
Physics-Informed Bayesian Optimization of Variational Quantum Circuits. NeurIPS (2023)
Christopher J. Anders, Leander Weber, David Neumann, Wojciech Samek, Klaus-Robert Müller, Sebastian Lapuschkin
Finding and removing Clever Hans: Using explanation methods to debug and improve deep models. Inf. Fusion 77 (2022)
Ann-Kathrin Dombrowski, Christopher J. Anders, Klaus-Robert Müller, Pan Kessel
Towards robust explanations for deep neural networks. Pattern Recognit. 121 (2022)
Frederik Pahde, Leander Weber, Christopher J. Anders, Wojciech Samek, Sebastian Lapuschkin
PatClArC: Using Pattern Concept Activation Vectors for Noise-Robust Model Debugging. CoRR (2022)
Christopher J. Anders, David Neumann, Wojciech Samek, Klaus-Robert Müller, Sebastian Lapuschkin
Software for Dataset-wide XAI: From Local Explanations to Global Insights with Zennit, CoRelAy, and ViRelAy. CoRR (2021)
Wojciech Samek, Grégoire Montavon, Sebastian Lapuschkin, Christopher J. Anders, Klaus-Robert Müller
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications. Proc. IEEE 109 (3) (2021)
Kim A. Nicoli, Christopher J. Anders, Lena Funcke, Tobias Hartung, Karl Jansen, Pan Kessel, Shinichi Nakajima, Paolo Stornati
Machine Learning of Thermodynamic Observables in the Presence of Mode Collapse. CoRR (2021)
Kim A. Nicoli, Christopher J. Anders, Lena Funcke, Tobias Hartung, Karl Jansen, Pan Kessel, Shinichi Nakajima, Paolo Stornati
On Estimation of Thermodynamic Observables in Lattice Field Theories with Deep Generative Models. CoRR (2020)
Ann-Kathrin Dombrowski, Christopher J. Anders, Klaus-Robert Müller, Pan Kessel
Towards Robust Explanations for Deep Neural Networks. CoRR (2020)
Christopher J. Anders, Plamen Pasliev, Ann-Kathrin Dombrowski, Klaus-Robert Müller, Pan Kessel
Fairwashing Explanations with Off-Manifold Detergent. CoRR (2020)
Christopher J. Anders, Plamen Pasliev, Ann-Kathrin Dombrowski, Klaus-Robert Müller, Pan Kessel
Fairwashing explanations with off-manifold detergent. ICML (2020)
Wojciech Samek, Grégoire Montavon, Sebastian Lapuschkin, Christopher J. Anders, Klaus-Robert Müller
Toward Interpretable Machine Learning: Transparent Deep Neural Networks and Beyond. CoRR (2020)
Ann-Kathrin Dombrowski, Maximilian Alber, Christopher J. Anders, Marcel Ackermann, Klaus-Robert Müller, Pan Kessel
Explanations can be manipulated and geometry is to blame. CoRR (2019)
Christopher J. Anders, Talmaj Marinc, David Neumann, Wojciech Samek, Klaus-Robert Müller, Sebastian Lapuschkin
Analyzing ImageNet with Spectral Relevance Analysis: Towards ImageNet un-Hans'ed. CoRR (2019)
Ann-Kathrin Dombrowski, Maximilian Alber, Christopher J. Anders, Marcel Ackermann, Klaus-Robert Müller, Pan Kessel
Explanations can be manipulated and geometry is to blame. NeurIPS (2019)
Christopher J. Anders, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller
Understanding Patch-Based Learning by Explaining Predictions. CoRR (2018)