3 accepted papers
Despite the increasing demand for safer machine learning practices, the use of Uncertainty Quantification (UQ) methods in production remains limited. This limitation is exacerbated by the challenge of validating UQ methods in absence of UQ ground truth. In classification tasks, when only a usual se…
In practice, data augmentation is assigned a predefined budget in terms of newly created samples per epoch. When using several types of data augmentation, the budget is usually uniformly distributed over the set of augmentations but one can wonder if this budget should not be allocated to each type…
The curse of dimensionality in particle filtering can be mitigated by approximating the posterior distribution by a product of marginals on disjoint low dimensional subspaces of the state space. One such approach is known as the block particle filter in which the correction and resampling steps in p…