A nonparametric method for gradual change problems with statistical guarantees

no code implementations • NeurIPS 2021 • Lizhen Nie, Dan Nicolae

We consider the detection and localization of gradual changes in the distribution of a sequence of time-ordered observations.

VCNet and Functional Targeted Regularization For Learning Causal Effects of Continuous Treatments

1 code implementation • 14 Mar 2021 • Lizhen Nie, Mao Ye, Qiang Liu, Dan Nicolae

Motivated by the rising abundance of observational data with continuous treatments, we investigate the problem of estimating the average dose-response curve (ADRF).

Varying Coefficient Neural Network with Functional Targeted Regularization for Estimating Continuous Treatment Effects

no code implementations • ICLR 2021 • Lizhen Nie, Mao Ye, Qiang Liu, Dan Nicolae

With the rising abundance of observational data with continuous treatments, we investigate the problem of estimating average dose-response curve (ADRF).

Estimation and inference in metabolomics with non-random missing data and latent factors

1 code implementation • 5 Sep 2019 • Chris McKennan, Carole Ober, Dan Nicolae

However, current methods to analyze these data can only account for the missing data or unobserved factors, but not both.

Methodology

Accounting for unobserved covariates with varying degrees of estimability in high dimensional biological data

1 code implementation • 3 Jan 2018 • Chris McKennan, Dan Nicolae

Lastly, we use previously published DNA methylation data to show our method can more accurately estimate the direct effect of asthma on methylation than previously published methods, which underestimate the correlation between asthma and latent cell type heterogeneity.

Methodology