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Differentiable and Transportable Structure Learning.

, , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 2206-2233. PMLR, (2023)

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Reimagining Synthetic Tabular Data Generation through Data-Centric AI: A Comprehensive Benchmark., , , and . CoRR, (2023)Data-IQ: Characterizing subgroups with heterogeneous outcomes in tabular data., , , and . NeurIPS, (2022)Automated machine vision enabled detection of movement disorders from hand drawn spirals., , and . ICHI, page 1-5. IEEE, (2020)DAUX: a Density-based Approach for Uncertainty eXplanations., , , , and . CoRR, (2022)Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations., , , , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 19497-19521. PMLR, (2022)Dissecting Sample Hardness: A Fine-Grained Analysis of Hardness Characterization Methods for Data-Centric AI., , and . CoRR, (2024)Can You Rely on Your Model Evaluation? Improving Model Evaluation with Synthetic Test Data., , , and . CoRR, (2023)TRIAGE: Characterizing and auditing training data for improved regression., , , and . CoRR, (2023)Data-SUITE: Data-centric identification of in-distribution incongruous examples., , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 19467-19496. PMLR, (2022)You can't handle the (dirty) truth: Data-centric insights improve pseudo-labeling., , , and . CoRR, (2024)