曼格拉维特和其他人. 答案答复答复答复

Same author

Scalable multi-group nonnegative spatial factorization for spatial genomics data with cell-type heterogeneity.

bioRxiv : the preprint server for biology·2026

Same author

Covariate-moderated Empirical Bayes Matrix Factorization.

Advances in neural information processing systems·2026

Same author

Segmentation-free analysis of live-cell imaging data reveals how T cell modifications influence cancer cell aggregation dynamics.

Scientific reports·2026

Same author

ebnm: An R Package for Solving the Empirical Bayes Normal Means Problem Using a Variety of Prior Families.

Journal of statistical software·2026

Same author

Machine Learning-Guided Discovery of Bacterial-Selective Membrane-Active Compounds Reveals Mechanistic Bias in Antibiotic Training Datasets.

bioRxiv : the preprint server for biology·2026

Same author

Empirical Bayes Covariance Decomposition, and a Solution to the Multiple Tuning Problem in Sparse PCA.

Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America·2026

相关实验视频

曼格拉维特和其他人. 答案答复答复答复

相关概念视频

Scalable multi-group nonnegative spatial factorization for spatial genomics data with cell-type heterogeneity.

Covariate-moderated Empirical Bayes Matrix Factorization.

Segmentation-free analysis of live-cell imaging data reveals how T cell modifications influence cancer cell aggregation dynamics.

ebnm: An R Package for Solving the Empirical Bayes Normal Means Problem Using a Variety of Prior Families.

Machine Learning-Guided Discovery of Bacterial-Selective Membrane-Active Compounds Reveals Mechanistic Bias in Antibiotic Training Datasets.

Empirical Bayes Covariance Decomposition, and a Solution to the Multiple Tuning Problem in Sparse PCA.

相关实验视频

曼格拉维特和其他人. 答案 答复 答复 答复

相关概念视频

相关文章

Scalable multi-group nonnegative spatial factorization for spatial genomics data with cell-type heterogeneity.

Covariate-moderated Empirical Bayes Matrix Factorization.

Segmentation-free analysis of live-cell imaging data reveals how T cell modifications influence cancer cell aggregation dynamics.

ebnm: An R Package for Solving the Empirical Bayes Normal Means Problem Using a Variety of Prior Families.

Machine Learning-Guided Discovery of Bacterial-Selective Membrane-Active Compounds Reveals Mechanistic Bias in Antibiotic Training Datasets.

Empirical Bayes Covariance Decomposition, and a Solution to the Multiple Tuning Problem in Sparse PCA.

曼格拉维特和其他人. 答案答复答复答复