Publications

Jonathan Crabbé, Pau Rodríguez, Vaishaal Shankar, Luca Zappella, Arno Blaas (2023). Robust multimodal models have outlier features and encode more concepts. In arXiv.

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Arthur Vandenhoeke, Lennert Antson, Guillem Ballesteros, Jonathan Crabbé, Michal Shimoni (2023). Explaining the Absorption Features of Deep Learning Hyperspectral Classification Models. In IGARSS 2023.

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Nabeel Seedat, Jonathan Crabbé, Zhaozhi Qian, Mihaela van der Schaar (2023). TRIAGE: Characterizing and auditing training data for improved regression. In NeurIPS 2023.

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Jonathan Crabbé, Mihaela van der Schaar (2023). Evaluating the Robustness of Interpretability Methods through Explanation Invariance and Equivariance. In NeurIPS 2023.

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Alan Jeffares, Tennison Liu, Jonathan Crabbé, Fergus Imrie, Mihaela van der Schaar (2023). TANGOS: Regularizing Tabular Neural Networks through Gradient Orthogonalization and Specialization. In ICLR 2023.

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Alan Jeffares, Tennison Liu, Jonathan Crabbé, Mihaela van der Schaar (2023). Joint Training of Deep Ensembles Fails Due to Learner Collusion. In NeurIPS 2023.

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Nabeel Seedat, Jonathan Crabbé, Ioana Bica, Mihaela van der Schaar (2022). Data-IQ: Characterizing subgroups with heterogeneous outcomes in tabular data. In NeurIPS 2022.

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Jonathan Crabbé, Mihaela van der Schaar (2022). Concept Activation Regions: A Generalized Framework For Concept-Based Explanations. In NeurIPS 2022.

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Jonathan Crabbé, Alicia Curth, Ioana Bica, Mihaela van der Schaar (2022). Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability. NeurIPS 2022 Datasets and Benchmarks Track.

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Jonathan Crabbé, Mihaela van der Schaar (2022). Label-Free Explainability for Unsupervised Models. In ICML 2022.

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Nabeel Seedat, Jonathan Crabbé, Mihaela van der Schaar (2022). Data-SUITE: Data-centric identification of in-distribution incongruous examples. In ICML 2022.

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Hao Sun, Boris van Breugel, Jonathan Crabbé, Nabeel Seedat, Mihaela van der Schaar (2022). Latent Density Models for Uncertainty Categorization. In NeurIPS 2023.

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Jonathan Crabbé, Zhaozhi Qian, Fergus Imrie, Mihaela van der Schaar (2021). Explaining Latent Representations with a Corpus of Examples. In NeurIPS 2021.

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Jonathan Crabbé, Mihaela van der Schaar (2021). Explaining Time Series Predictions with Dynamic Masks. In ICML 2021.

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Jonathan Crabbé, Yao Zhang, William R. Zame, Mihaela van der Schaar (2020). Learning outside the black-box: the pursuit of interpretable models. In NeurIPS 2020.

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