Thomas Fel
According to our database1,
Thomas Fel
authored at least 34 papers
between 2020 and 2024.
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Bibliography
2024
AI Ethics, February, 2024
CoRR, 2024
CoRR, 2024
CoRR, 2024
CoRR, 2024
CoRR, 2024
Proceedings of the Explainable Artificial Intelligence, 2024
Saliency strikes back: How filtering out high frequencies improves white-box explanations.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
2023
CoRR, 2023
Unlocking Feature Visualization for Deeper Networks with MAgnitude Constrained Optimization.
CoRR, 2023
Performance-optimized deep neural networks are evolving into worse models of inferotemporal visual cortex.
CoRR, 2023
Adversarial alignment: Breaking the trade-off between the strength of an attack and its relevance to human perception.
CoRR, 2023
COCKATIEL: COntinuous Concept ranKed ATtribution with Interpretable ELements for explaining neural net classifiers on NLP tasks.
CoRR, 2023
On the explainable properties of 1-Lipschitz Neural Networks: An Optimal Transport Perspective.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Performance-optimized deep neural networks are evolving into worse models of inferotemporal visual cortex.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Unlocking Feature Visualization for Deep Network with MAgnitude Constrained Optimization.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
A Holistic Approach to Unifying Automatic Concept Extraction and Concept Importance Estimation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
Don't Lie to Me! Robust and Efficient Explainability with Verified Perturbation Analysis.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
Confident Object Detection via Conformal Prediction and Conformal Risk Control: an Application to Railway Signaling.
Proceedings of the Conformal and Probabilistic Prediction with Applications, 2023
COCKATIEL: COntinuous Concept ranKed ATtribution with Interpretable ELements for explaining neural net classifiers on NLP.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023
2022
CoRR, 2022
CoRR, 2022
How Good is your Explanation? Algorithmic Stability Measures to Assess the Quality of Explanations for Deep Neural Networks.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022
Making Sense of Dependence: Efficient Black-box Explanations Using Dependence Measure.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
What I Cannot Predict, I Do Not Understand: A Human-Centered Evaluation Framework for Explainability Methods.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
2021
Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
2020
CoRR, 2020