Thomas Fel
According to our database1,
Thomas Fel
authored at least 26 papers
between 2020 and 2024.
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Bibliography
2024
CoRR, 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