Crabbé, Jonathan

16 publications

AISTATS 2024 DAGnosis: Localized Identification of Data Inconsistencies Using Structures Nicolas Huynh, Jeroen Berrevoets, Nabeel Seedat, Jonathan Crabbé, Zhaozhi Qian, Mihaela Schaar

TMLR 2024 Interpreting CLIP: Insights on the Robustness to ImageNet Distribution Shifts Jonathan Crabbé, Pau Rodriguez, Vaishaal Shankar, Luca Zappella, Arno Blaas

ICML 2024 Time Series Diffusion in the Frequency Domain Jonathan Crabbé, Nicolas Huynh, Jan Pawel Stanczuk, Mihaela Van Der Schaar

NeurIPS 2023 Evaluating the Robustness of Interpretability Methods Through Explanation Invariance and Equivariance Jonathan Crabbé, Mihaela van der Schaar

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

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

NeurIPS 2023 TRIAGE: Characterizing and Auditing Training Data for Improved Regression Nabeel Seedat, Jonathan Crabbé, Zhaozhi Qian, Mihaela van der Schaar

NeurIPS 2023 What Is Flagged in Uncertainty Quantification? Latent Density Models for Uncertainty Categorization Hao Sun, Boris van Breugel, Jonathan Crabbé, Nabeel Seedat, Mihaela van der Schaar

NeurIPS 2022 Benchmarking Heterogeneous Treatment Effect Models Through the Lens of Interpretability Jonathan Crabbé, Alicia Curth, Ioana Bica, Mihaela van der Schaar

NeurIPS 2022 Concept Activation Regions: A Generalized Framework for Concept-Based Explanations Jonathan Crabbé, Mihaela van der Schaar

NeurIPS 2022 Data-IQ: Characterizing Subgroups with Heterogeneous Outcomes in Tabular Data Nabeel Seedat, Jonathan Crabbé, Ioana Bica, Mihaela van der Schaar

ICML 2022 Data-SUITE: Data-Centric Identification of In-Distribution Incongruous Examples Nabeel Seedat, Jonathan Crabbé, Mihaela Schaar

ICML 2022 Label-Free Explainability for Unsupervised Models Jonathan Crabbé, Mihaela Schaar

NeurIPS 2021 Explaining Latent Representations with a Corpus of Examples Jonathan Crabbe, Zhaozhi Qian, Fergus Imrie, Mihaela van der Schaar

ICML 2021 Explaining Time Series Predictions with Dynamic Masks Jonathan Crabbé, Mihaela Van Der Schaar

NeurIPS 2020 Learning Outside the Black-Box: The Pursuit of Interpretable Models Jonathan Crabbe, Yao Zhang, William Zame, Mihaela van der Schaar