12 citations · 31 across the 9 of their papers we have counts for
6 papers · 1 filter
Tailored Bayes: a risk modelling framework under unequal misclassification costs
Solon Karapanagiotis, Umberto Benedetto, Sach Mukherjee +2
Risk prediction models are a crucial tool in healthcare. Risk prediction models with a binary outcome (i.e., binary classification models) are often constructed using methodology w…
Evaluation of Causal Structure Learning Algorithms via Risk Estimation
Marco F. Eigenmann, Sach Mukherjee, Marloes H. Maathuis
Recent years have seen many advances in methods for causal structure learning from data. The empirical assessment of such methods, however, is much less developed. Motivated by thi…
High-dimensional regression in practice: an empirical study of finite-sample prediction, variable selection and ranking
Fan Wang, Sach Mukherjee, Sylvia Richardson +1
Penalized likelihood approaches are widely used for high-dimensional regression. Although many methods have been proposed and the associated theory is now well-developed, the relat…
Discussion of "Causal inference using invariant prediction: identification and confidence intervals" by Peters, Bühlmann and Meinshausen
Chris J. Oates, Jessica Kasza, Sach Mukherjee
Contribution to the discussion of the paper "Causal inference using invariant prediction: identification and confidence intervals" by Peters, Bühlmann and Meinshausen, to appear in…
Inferring network structure from interventional time-course experiments
Simon E. F. Spencer, Steven M. Hill, Sach Mukherjee
Graphical models are widely used to study biological networks. Interventions on network nodes are an important feature of many experimental designs for the study of biological netw…
Two-Sample Testing in High-Dimensional Models
Nicolas Städler, Sach Mukherjee
We propose novel methodology for testing equality of model parameters between two high-dimensional populations. The technique is very general and applicable to a wide range of mode…