Causal Effects with Hidden Treatment Diffusion on Observed or Partially Observed Networks. (arXiv:2109.07502v1 [stat.ME]) arxiv.org/abs/2109.07502

RaWaNet: Enriching Graph Neural Network Input via Random Walks on Graphs. (arXiv:2109.07555v1 [stat.ML]) arxiv.org/abs/2109.07555

Bivariate Hierarchical Bayesian Model for Combining Summary Measures and their Uncertainties from Multiple Sources. (arXiv:2109.07560v1 [stat.ME]) arxiv.org/abs/2109.07560

Non-smooth Bayesian Optimization in Tuning Problems. (arXiv:2109.07563v1 [cs.LG]) arxiv.org/abs/2109.07563

Testing the efficacy of epidemic testing. (arXiv:2109.07580v1 [physics.soc-ph]) arxiv.org/abs/2109.07580

The Impact of COVID-19 on Sports Betting Markets. (arXiv:2109.07581v1 [physics.soc-ph]) arxiv.org/abs/2109.07581

Direct estimation of differential Granger causality between two high-dimensional time series. (arXiv:2109.07609v1 [stat.ME]) arxiv.org/abs/2109.07609

BacHMMachine: An Interpretable and Scalable Model for Algorithmic Harmonization for Four-part Baroque Chorales. (arXiv:2109.07623v1 [cs.SD]) arxiv.org/abs/2109.07623

How trustworthy is your tree? Bayesian phylogenetic effective sample size through the lens of Monte Carlo error. (arXiv:2109.07629v1 [stat.ME]) arxiv.org/abs/2109.07629

Semi-parametric estimation of the EASI model: Welfare implications of taxes identifying clusters due to unobserved preference heterogeneity. (arXiv:2109.07646v1 [econ.EM]) arxiv.org/abs/2109.07646

Learning and Decision-Making with Data: Optimal Formulations and Phase Transitions. (arXiv:2109.06911v1 [stat.ML]) arxiv.org/abs/2109.06911

Spatiotemporal Characterization of VIIRS Night Light. (arXiv:2109.06913v1 [physics.geo-ph]) arxiv.org/abs/2109.06913

Reconstruction on Trees and Low-Degree Polynomials. (arXiv:2109.06915v1 [math.PR]) arxiv.org/abs/2109.06915

Choosing an Optimal Method for Causal Decomposition Analysis: A Better Practice for Identifying Contributing Factors to Health Disparities. (arXiv:2109.06940v1 [stat.ME]) arxiv.org/abs/2109.06940

Learning trends of COVID-19 using semi-supervised clustering. (arXiv:2109.06955v1 [stat.AP]) arxiv.org/abs/2109.06955

Proximal Causal Inference for Complex Longitudinal Studies. (arXiv:2109.07030v1 [stat.ME]) arxiv.org/abs/2109.07030

Learning delay dynamics for multivariate stochastic processes, with application to the prediction of the growth rate of COVID-19 cases in the United States. (arXiv:2109.07059v1 [math.AP]) arxiv.org/abs/2109.07059

Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Streaming Data. (arXiv:2109.07117v1 [cs.LG]) arxiv.org/abs/2109.07117

Bayesian testing of linear versus nonlinear effects using Gaussian process priors. (arXiv:2109.07166v1 [stat.ME]) arxiv.org/abs/2109.07166

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