Christopher J. Anders

28 papers A* 6Journal 19Unranked 1
YearRankTypeTitle / Venue / Authors
2025 J jnl
Adaptive Observation Cost Control for Variational Quantum Eigensolvers.
CoRR
Christopher J. Anders, Kim A. Nicoli, Bingting Wu, Naima Elosegui, Samuele Pedrielli, Lena Funcke, Karl Jansen, Stefan Kühn, Shinichi Nakajima
2025 J jnl
Bayesian Parameter Shift Rule in Variational Quantum Eigensolvers.
CoRR
Samuele Pedrielli, Christopher J. Anders, Lena Funcke, Karl Jansen, Kim A. Nicoli, Shinichi Nakajima
2025 A* conf
Navigating Neural Space: Revisiting Concept Activation Vectors to Overcome Directional Divergence.
ICLR
Frederik Pahde, Maximilian Dreyer, Moritz Weckbecker, Leander Weber, Christopher J. Anders, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin
2024 A* conf
Adaptive Observation Cost Control for Variational Quantum Eigensolvers.
ICML
Christopher J. Anders, Kim Andrea Nicoli, Bingting Wu, Naima Elosegui, Samuele Pedrielli, Lena Funcke, Karl Jansen, Stefan Kühn, Shinichi Nakajima
2024 — —
Debugging learning algorithms: understanding and correcting machine learning models.
Christopher J. Anders
2024 A* conf
From Hope to Safety: Unlearning Biases of Deep Models via Gradient Penalization in Latent Space.
AAAI
Maximilian Dreyer, Frederik Pahde, Christopher J. Anders, Wojciech Samek, Sebastian Lapuschkin
2024 J jnl
Physics-Informed Bayesian Optimization of Variational Quantum Circuits.
CoRR
Kim A. Nicoli, Christopher J. Anders, Lena Funcke, Tobias Hartung, Karl Jansen, Stefan Kühn, Klaus-Robert Müller, Paolo Stornati, Pan Kessel, Shinichi Nakajima
2023 J jnl
Detecting and Mitigating Mode-Collapse for Flow-based Sampling of Lattice Field Theories.
CoRR
Kim A. Nicoli, Christopher J. Anders, Tobias Hartung, Karl Jansen, Pan Kessel, Shinichi Nakajima
2023 J jnl
From Hope to Safety: Unlearning Biases of Deep Models by Enforcing the Right Reasons in Latent Space.
CoRR
Maximilian Dreyer, Frederik Pahde, Christopher J. Anders, Wojciech Samek, Sebastian Lapuschkin
2023 A* conf
Physics-Informed Bayesian Optimization of Variational Quantum Circuits.
NeurIPS
Kim Nicoli, Christopher J. Anders, Lena Funcke, Tobias Hartung, Karl Jansen, Stefan Kühn, Klaus-Robert Müller, Paolo Stornati, Pan Kessel, Shinichi Nakajima
2023 — conf
Towards Fixing Clever-Hans Predictors with Counterfactual Knowledge Distillation.
ICCV (Workshops)
Sidney Bender, Christopher J. Anders, Pattarawat Chormai, Heike Marxfeld, Jan Herrmann, Grégoire Montavon
2023 J jnl
Towards Fixing Clever-Hans Predictors with Counterfactual Knowledge Distillation.
CoRR
Sidney Bender, Christopher J. Anders, Pattarawat Chormai, Heike Marxfeld, Jan Herrmann, Grégoire Montavon
2022 J jnl
Finding and removing Clever Hans: Using explanation methods to debug and improve deep models.
Inf. Fusion
Christopher J. Anders, Leander Weber, David Neumann, Wojciech Samek, Klaus-Robert Müller, Sebastian Lapuschkin
2022 J jnl
PatClArC: Using Pattern Concept Activation Vectors for Noise-Robust Model Debugging.
CoRR
Frederik Pahde, Leander Weber, Christopher J. Anders, Wojciech Samek, Sebastian Lapuschkin
2022 J jnl
Towards robust explanations for deep neural networks.
Pattern Recognit.
Ann-Kathrin Dombrowski, Christopher J. Anders, Klaus-Robert Müller, Pan Kessel
2021 J jnl
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications.
Proc. IEEE
Wojciech Samek, Grégoire Montavon, Sebastian Lapuschkin, Christopher J. Anders, Klaus-Robert Müller
2021 J jnl
Machine Learning of Thermodynamic Observables in the Presence of Mode Collapse.
CoRR
Kim A. Nicoli, Christopher J. Anders, Lena Funcke, Tobias Hartung, Karl Jansen, Pan Kessel, Shinichi Nakajima, Paolo Stornati
2021 J jnl
Software for Dataset-wide XAI: From Local Explanations to Global Insights with Zennit, CoRelAy, and ViRelAy.
CoRR
Christopher J. Anders, David Neumann, Wojciech Samek, Klaus-Robert Müller, Sebastian Lapuschkin
2020 J jnl
Fairwashing Explanations with Off-Manifold Detergent.
CoRR
Christopher J. Anders, Plamen Pasliev, Ann-Kathrin Dombrowski, Klaus-Robert Müller, Pan Kessel
2020 A* conf
Fairwashing explanations with off-manifold detergent.
ICML
Christopher J. Anders, Plamen Pasliev, Ann-Kathrin Dombrowski, Klaus-Robert Müller, Pan Kessel
2020 J jnl
On Estimation of Thermodynamic Observables in Lattice Field Theories with Deep Generative Models.
CoRR
Kim A. Nicoli, Christopher J. Anders, Lena Funcke, Tobias Hartung, Karl Jansen, Pan Kessel, Shinichi Nakajima, Paolo Stornati
2020 J jnl
Toward Interpretable Machine Learning: Transparent Deep Neural Networks and Beyond.
CoRR
Wojciech Samek, Grégoire Montavon, Sebastian Lapuschkin, Christopher J. Anders, Klaus-Robert Müller
2020 J jnl
Towards Robust Explanations for Deep Neural Networks.
CoRR
Ann-Kathrin Dombrowski, Christopher J. Anders, Klaus-Robert Müller, Pan Kessel
2019 J jnl
Analyzing ImageNet with Spectral Relevance Analysis: Towards ImageNet un-Hans'ed.
CoRR
Christopher J. Anders, Talmaj Marinc, David Neumann, Wojciech Samek, Klaus-Robert Müller, Sebastian Lapuschkin
2019 A* conf
Explanations can be manipulated and geometry is to blame.
NeurIPS
Ann-Kathrin Dombrowski, Maximilian Alber, Christopher J. Anders, Marcel Ackermann, Klaus-Robert Müller, Pan Kessel
2019 J jnl
Explanations can be manipulated and geometry is to blame.
CoRR
Ann-Kathrin Dombrowski, Maximilian Alber, Christopher J. Anders, Marcel Ackermann, Klaus-Robert Müller, Pan Kessel
2019 — ch.
Understanding Patch-Based Learning of Video Data by Explaining Predictions.
Explainable AI
Christopher J. Anders, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller
2018 J jnl
Understanding Patch-Based Learning by Explaining Predictions.
CoRR
Christopher J. Anders, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller