14 citations · 25 across the 6 of their papers we have counts for
6 papers
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…
Model-based clustering in very high dimensions via adaptive projections
Bernd Taschler, Frank Dondelinger, Sach Mukherjee
Mixture models are a standard approach to dealing with heterogeneous data with non-i.i.d. structure. However, when the dimension is large relative to sample size and where…
High-dimensional regression over disease subgroups
Frank Dondelinger, Sach Mukherjee, The Alzheimer's Disease Neuroimaging Initiative
We consider high-dimensional regression over subgroups of observations. Our work is motivated by biomedical problems, where disease subtypes, for example, may differ with respect t…
Estimating causal structure using conditional DAG models
Chris J. Oates, Jim Q. Smith, Sach Mukherjee
This paper considers inference of causal structure in a class of graphical models called "conditional DAGs". These are directed acyclic graph (DAG) models with two kinds of variabl…
Exact Estimation of Multiple Directed Acyclic Graphs
Chris J. Oates, Jim Q. Smith, Sach Mukherjee +1
This paper considers the problem of estimating the structure of multiple related directed acyclic graph (DAG) models. Building on recent developments in exact estimation of DAGs us…
On the relationship between ODEs and DBNs
Chris. J. Oates, Steven. M. Hill, Sach Mukherjee
Recently, Li et al. (Bioinformatics 27(19), 2686-91, 2011) proposed a method, called Differential Equation-based Local Dynamic Bayesian Network (DELDBN), for reverse engineering ge…