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gregoire pacreau

2 accepted papers

2024

Neural Conditional Probability for Uncertainty Quantification

NeurIPS 2024poster

We introduce Neural Conditional Probability (NCP), an operator-theoretic approach to learning conditional distributions with a focus on statistical inference tasks. NCP can be used to build conditional confidence regions and extract key statistics such as conditional quantiles, mean, and covarianc…

Cited by 0SourcePDFScholar
2023

Robust covariance estimation with missing values and cell-wise contamination

NeurIPS 2023poster

Large datasets are often affected by cell-wise outliers in the form of missing or erroneous data. However, discarding any samples containing outliers may result in a dataset that is too small to accurately estimate the covariance matrix. Moreover, the robust procedures designed to address this probl…