Accelerating Ensemble Error Bar Prediction with Single Models Fits

arXiv:2404.09896v1 Announce Type: new
Abstract: Ensemble models can be used to estimate prediction uncertainties in machine learning models. However, an ensemble of N models is approximately N times more computationally demanding compared to a single model when it is used for inference. In this work, we explore fitting a single model to predicted ensemble error bar data, which allows us to estimate uncertainties without the need for a full ensemble. Our approach is based on three models: Model A for …

abstract arxiv cond-mat.mtrl-sci cs.lg ensemble error explore however inference machine machine learning machine learning models prediction type work