Jonathan Crabbé

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 33

Top Topics

Rotational Invariant

Top Venues

Publications

Boris van Breugel, Jonathan Crabbé, Rob Davis, Mihaela van der Schaar
LaTable: Towards Large Tabular Models. CoRR (2024)
Jonathan Crabbé, Nicolas Huynh, Jan Stanczuk, Mihaela van der Schaar
Time Series Diffusion in the Frequency Domain. CoRR (2024)
Nicolas Huynh, Jeroen Berrevoets, Nabeel Seedat, Jonathan Crabbé, Zhaozhi Qian, Mihaela van der Schaar
DAGnosis: Localized Identification of Data Inconsistencies using Structures. AISTATS (2024)
Nicolas Huynh, Jeroen Berrevoets, Nabeel Seedat, Jonathan Crabbé, Zhaozhi Qian, Mihaela van der Schaar
DAGnosis: Localized Identification of Data Inconsistencies using Structures. CoRR (2024)
Jonathan Crabbé, Pau Rodríguez, Vaishaal Shankar, Luca Zappella, Arno Blaas
Robust multimodal models have outlier features and encode more concepts. CoRR (2023)
Nabeel Seedat, Jonathan Crabbé, Zhaozhi Qian, Mihaela van der Schaar
TRIAGE: Characterizing and auditing training data for improved regression. NeurIPS (2023)
Alan Jeffares, Tennison Liu, Jonathan Crabbé, Mihaela van der Schaar
Joint Training of Deep Ensembles Fails Due to Learner Collusion. NeurIPS (2023)
Alan Jeffares, Tennison Liu, Jonathan Crabbé, Fergus Imrie, Mihaela van der Schaar
TANGOS: Regularizing Tabular Neural Networks through Gradient Orthogonalization and Specialization. ICLR (2023)
Hao Sun, Boris van Breugel, Jonathan Crabbé, Nabeel Seedat, Mihaela van der Schaar
What is Flagged in Uncertainty Quantification? Latent Density Models for Uncertainty Categorization. NeurIPS (2023)
Jonathan Crabbé, Mihaela van der Schaar
Evaluating the Robustness of Interpretability Methods through Explanation Invariance and Equivariance. NeurIPS (2023)
Alan Jeffares, Tennison Liu, Jonathan Crabbé, Mihaela van der Schaar
Joint Training of Deep Ensembles Fails Due to Learner Collusion. CoRR (2023)
Nabeel Seedat, Jonathan Crabbé, Zhaozhi Qian, Mihaela van der Schaar
TRIAGE: Characterizing and auditing training data for improved regression. CoRR (2023)
Jonathan Crabbé, Mihaela van der Schaar
Evaluating the Robustness of Interpretability Methods through Explanation Invariance and Equivariance. CoRR (2023)
Claudio Zeni, Robert Pinsler, Daniel Zügner, Andrew Fowler, Matthew Horton, Xiang Fu, Sasha Shysheya, Jonathan Crabbé, Lixin Sun, Jake Smith, Ryota Tomioka, Tian Xie
MatterGen: a generative model for inorganic materials design. CoRR (2023)
Arthur Vandenhoeke, Lennert Antson, Guillem Ballesteros, Jonathan Crabbé, Michal Shimoni
Explaining the Absorption Features of Deep Learning Hyperspectral Classification Models. IGARSS (2023)
Alan Jeffares, Tennison Liu, Jonathan Crabbé, Fergus Imrie, Mihaela van der Schaar
TANGOS: Regularizing Tabular Neural Networks through Gradient Orthogonalization and Specialization. CoRR (2023)
Jonathan Crabbé, Alicia Curth, Ioana Bica, Mihaela van der Schaar
Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability. NeurIPS (2022)
Nabeel Seedat, Jonathan Crabbé, Mihaela van der Schaar
Data-SUITE: Data-centric identification of in-distribution incongruous examples. ICML (2022)
Jonathan Crabbé, Mihaela van der Schaar
Concept Activation Regions: A Generalized Framework For Concept-Based Explanations. CoRR (2022)
Nabeel Seedat, Jonathan Crabbé, Ioana Bica, Mihaela van der Schaar
Data-IQ: Characterizing subgroups with heterogeneous outcomes in tabular data. NeurIPS (2022)
Jonathan Crabbé, Mihaela van der Schaar
Label-Free Explainability for Unsupervised Models. ICML (2022)
Jonathan Crabbé, Mihaela van der Schaar
Label-Free Explainability for Unsupervised Models. CoRR (2022)
Hao Sun, Boris van Breugel, Jonathan Crabbé, Nabeel Seedat, Mihaela van der Schaar
DAUX: a Density-based Approach for Uncertainty eXplanations. CoRR (2022)
Nabeel Seedat, Jonathan Crabbé, Mihaela van der Schaar
Data-SUITE: Data-centric identification of in-distribution incongruous examples. CoRR (2022)
Jonathan Crabbé, Alicia Curth, Ioana Bica, Mihaela van der Schaar
Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability. CoRR (2022)
Jonathan Crabbé, Mihaela van der Schaar
Concept Activation Regions: A Generalized Framework For Concept-Based Explanations. NeurIPS (2022)
Nabeel Seedat, Jonathan Crabbé, Ioana Bica, Mihaela van der Schaar
Data-IQ: Characterizing subgroups with heterogeneous outcomes in tabular data. CoRR (2022)
Jonathan Crabbé, Zhaozhi Qian, Fergus Imrie, Mihaela van der Schaar
Explaining Latent Representations with a Corpus of Examples. NeurIPS (2021)
Jonathan Crabbé, Mihaela van der Schaar
Explaining Time Series Predictions with Dynamic Masks. ICML (2021)
Jonathan Crabbé, Zhaozhi Qian, Fergus Imrie, Mihaela van der Schaar
Explaining Latent Representations with a Corpus of Examples. CoRR (2021)
Jonathan Crabbé, Mihaela van der Schaar
Explaining Time Series Predictions with Dynamic Masks. CoRR (2021)
Jonathan Crabbé, Yao Zhang, William R. Zame, Mihaela van der Schaar
Learning outside the Black-Box: The pursuit of interpretable models. NeurIPS (2020)
Jonathan Crabbé, Yao Zhang, William R. Zame, Mihaela van der Schaar
Learning outside the Black-Box: The pursuit of interpretable models. CoRR (2020)