4 papers
Distributional Conformal Prediction for Markov Processes
Dehao Dai, Kejin Wu, Dimitris N. Politis
We introduce the Markov Distributional Conformal Prediction (MDCP) method that extends the distributional conformal prediction (previously developed for regression) to the setting…
Calibration Prediction Interval for Non-parametric Regression and Neural Networks
Kejin Wu, Dimitris N. Politis
Accurate conditional prediction in the regression setting plays an important role in many real-world problems. Typically, a point prediction often falls short since no attempt is m…
Deep Limit Model-free Prediction in Regression
Kejin Wu, Dimitris N. Politis
In this paper, we provide a novel Model-free approach based on Deep Neural Network (DNN) to accomplish point prediction and prediction interval under a general regression setting.…
Scalable Subsampling Inference for Deep Neural Networks
Kejin Wu, Dimitris N. Politis
Deep neural networks (DNN) has received increasing attention in machine learning applications in the last several years. Recently, a non-asymptotic error bound has been developed t…