10 citations · 21 across the 7 of their papers we have counts for
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stat.ML2023
Wasserstein Generative Regression
Shanshan Song, Tong Wang, Guohao Shen +2
In this paper, we propose a new and unified approach for nonparametric regression and conditional distribution learning. Our approach simultaneously estimates a regression function…
stat.ML2023
Differentiable Neural Networks with RePU Activation: with Applications to Score Estimation and Isotonic Regression
Guohao Shen, Yuling Jiao, Yuanyuan Lin +1
We study the properties of differentiable neural networks activated by rectified power unit (RePU) functions. We show that the partial derivatives of RePU neural networks can be re…
stat.ML2022★ 1 cited
Nonparametric Quantile Regression: Non-Crossing Constraints and Conformal Prediction
Wenlu Tang, Guohao Shen, Yuanyuan Lin +1
We propose a nonparametric quantile regression method using deep neural networks with a rectified linear unit penalty function to avoid quantile crossing. This penalty function is…