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Jonathan Crabbé
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Year
Explaining Time Series Predictions with Dynamic Masks
J Crabbé, M van der Schaar
Proceedings of the 38th International Conference on Machine Learning, 2021
552021
Explaining Latent Representations with a Corpus of Examples
J Crabbé, Z Qian, F Imrie, M van der Schaar
Proceedings of the 35th International Conference on Neural Information …, 2021
372021
Learning outside the Black-Box: The pursuit of interpretable models
J Crabbe, Y Zhang, W Zame, M van der Schaar
Proceedings of the 34th International Conference on Neural Information …, 2020
242020
Concept Activation Regions: A Generalized Framework For Concept-Based Explanations
J Crabbé, M van der Schaar
Proceedings of the 36th International Conference on Neural Information …, 2022
212022
Label-Free Explainability for Unsupervised Models
J Crabbé, M van der Schaar
Proceedings of the 39th International Conference on Machine Learning, 2022
202022
Mattergen: a generative model for inorganic materials design
C Zeni, R Pinsler, D Zügner, A Fowler, M Horton, X Fu, S Shysheya, ...
arXiv preprint arXiv:2312.03687, 2023
182023
Data-IQ: Characterizing subgroups with heterogeneous outcomes in tabular data
N Seedat, J Crabbé, I Bica, M van der Schaar
Proceedings of the 36th International Conference on Neural Information …, 2022
172022
Data-SUITE: Data-centric identification of in-distribution incongruous examples
N Seedat, J Crabbe, M van der Schaar
Proceedings of the 39th International Conference on Machine Learning, 2022
162022
Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability
J Crabbé, A Curth, I Bica, M van der Schaar
Proceedings of the Neural Information Processing Systems Track on Datasets …, 2022
132022
TANGOS: Regularizing Tabular Neural Networks through Gradient Orthogonalization and Specialization
A Jeffares, T Liu, J Crabbé, F Imrie, M van der Schaar
The Eleventh International Conference on Learning Representations, 2023
102023
What is Flagged in Uncertainty Quantification? Latent Density Models for Uncertainty Categorization
H Sun, B van Breugel, J Crabbé, N Seedat, M van der Schaar
Proceedings of the 37th International Conference on Neural Information …, 2023
6*2023
Joint Training of Deep Ensembles Fails Due to Learner Collusion
A Jeffares, T Liu, J Crabbé, M van der Schaar
Proceedings of the 37th International Conference on Neural Information …, 2023
52023
TRIAGE: Characterizing and auditing training data for improved regression
N Seedat, J Crabbé, Z Qian, M van der Schaar
Proceedings of the 37th International Conference on Neural Information …, 2023
32023
Evaluating the Robustness of Interpretability Methods through Explanation Invariance and Equivariance
J Crabbé, M van der Schaar
Proceedings of the 37th International Conference on Neural Information …, 2023
32023
Time Series Diffusion in the Frequency Domain
J Crabbé, N Huynh, J Stanczuk, M van der Schaar
arXiv preprint arXiv:2402.05933, 2024
12024
DAGnosis: Localized Identification of Data Inconsistencies using Structures
N Huynh, J Berrevoets, N Seedat, J Crabbé, Z Qian, M van der Schaar
arXiv preprint arXiv:2402.17599, 2024
2024
Robust multimodal models have outlier features and encode more concepts
J Crabbé, P Rodríguez, V Shankar, L Zappella, A Blaas
arXiv preprint arXiv:2310.13040, 2023
2023
Explaining the Absorption Features of Deep Learning Hyperspectral Classification Models
A Vandenhoeke, L Antson, G Ballesteros, J Crabbé, M Shimoni
IGARSS 2023-2023 IEEE International Geoscience and Remote Sensing Symposium …, 2023
2023
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