Efficient Learning of Minimal Volume Uncertainty Ellipsoids for Parameter Estimation

The optimal uncertainty ellipsoids are centered around the conditional mean and shaped as the conditional covariance matrix under the assumption of jointly Gaussian data. For more practical cases, a differentiable optimization approach using a neural network can approximately compute the optimal ellipsoids with less storage and fewer computations at inference time, leading to accurate yet smaller ellipsoids.