112 citations · 277 across the 35 of their papers we have counts for
37 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…
Multi-step ahead prediction intervals for non-parametric autoregressions via bootstrap: consistency, debiasing and pertinence
Dimitris N. Politis, Kejin Wu
To address the difficult problem of multi-step ahead prediction of non-parametric autoregressions, we consider a forward bootstrap approach. Employing a local constant estimator, w…
Bootstrap Prediction Inference of Non-linear Autoregressive Models
Kejin Wu, Dimitris N. Politis
The non-linear autoregressive (NLAR) model plays an important role in modeling and predicting time series. One-step ahead prediction is straightforward using the NLAR model, but th…