Publications

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

PDF Cite Code Project

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

PDF Cite Code Project Project

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.

PDF Cite Code Project Project

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

PDF Cite Code Project Project Video

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

PDF Cite Project

Hao Sun, Boris van Breugel, Jonathan Crabbé, Nabeel Seedat, Mihaela van der Schaar (2022). DAUX: a Density-based Approach for Uncertainty eXplanations. In ICML 2022 DFUQ Workshop.

PDF Cite Project Project

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

PDF Cite Code Project Video

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

PDF Cite Code Project Video

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.

PDF Cite Code Project Video