Sach Mukherjee

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 21

Top Topics

High Dimensions

Causal Structure

Undirected Graph

Conditional Independence Tests

Top Venues

J. Mach. Learn. Res.

Publications

Luka Kovacevic, Izzy Newsham, Sach Mukherjee, John Whittaker
Simulation-based Benchmarking for Causal Structure Learning in Gene Perturbation Experiments. CoRR (2024)
Kai Lagemann, Christian Lagemann, Sach Mukherjee
Invariance-based Learning of Latent Dynamics. ICLR (2024)
Konstantinos Perrakis, Thomas Lartigue, Frank Dondelinger, Sach Mukherjee
Regularized Joint Mixture Models. J. Mach. Learn. Res. 24 (2023)
Kai Lagemann, Christian Lagemann, Bernd Taschler, Sach Mukherjee
Deep learning of causal structures in high dimensions under data limitations. Nat. Mac. Intell. 5 (11) (2023)
Kai Lagemann, Christian Lagemann, Sach Mukherjee
Learning Latent Dynamics via Invariant Decomposition and (Spatio-)Temporal Transformers. CoRR (2023)
Robin Richter, Shankar Bhamidi, Sach Mukherjee
Improved baselines for causal structure learning on interventional data. Stat. Comput. 33 (5) (2023)
Kai Lagemann, Christian Lagemann, Bernd Taschler, Sach Mukherjee
Deep Learning of Causal Structures in High Dimensions. CoRR (2022)
Thomas Lartigue, Sach Mukherjee
Scalable Regularised Joint Mixture Models. CoRR (2022)
Thomas Lartigue, Sach Mukherjee
On unsupervised projections and second order signals. CoRR (2022)
Konstantin Göbler, Anne Miloschewski, Mathias Drton, Sach Mukherjee
High-Dimensional Undirected Graphical Models for Arbitrary Mixed Data. CoRR (2022)
Christian Lagemann, Kai Lagemann, Sach Mukherjee, Wolfgang Schröder
Deep recurrent optical flow learning for particle image velocimetry data. Nat. Mach. Intell. 3 (7) (2021)
Marco Eigenmann, Sach Mukherjee, Marloes H. Maathuis
Evaluation of Causal Structure Learning Algorithms via Risk Estimation. UAI (2020)
Fan Wang, Sach Mukherjee, Sylvia Richardson, Steven M. Hill
High-dimensional regression in practice: an empirical study of finite-sample prediction, variable selection and ranking. Stat. Comput. 30 (3) (2020)
Steven M. Hill, Chris J. Oates, Duncan A. J. Blythe, Sach Mukherjee
Causal Learning via Manifold Regularization. J. Mach. Learn. Res. 20 (2019)
Bernd Taschler, Frank Dondelinger, Sach Mukherjee
Model-based clustering in very high dimensions via adaptive projections. CoRR (2019)
Umberto Noè, Bernd Taschler, Joachim Täger, Peter Heutink, Sach Mukherjee
Ancestral causal learning in high dimensions with a human genome-wide application. CoRR (2019)
Gerard Sanroma, Loes Rutten-Jacobs, Valerie Lohner, Johanna Kramme, Sach Mukherjee, Martin Reuter, Tony Stöcker, Monique M. B. Breteler
SCCA-Ref: Novel Sparse Canonical Correlation Analysis with Reference to Discover Independent Spatial Associations Between White Matter Hyperintensities and Atrophy. MLMI@MICCAI (2018)
Nicolas Städler, Frank Dondelinger, Steven M. Hill, Rehan Akbani, Yiling Lu, Gordon B. Mills, Sach Mukherjee
Molecular heterogeneity at the network level: high-dimensional testing, clustering and a TCGA case study. Bioinform. 33 (18) (2017)
Robert J. B. Goudie, Sach Mukherjee
A Gibbs Sampler for Learning DAGs. J. Mach. Learn. Res. 17 (2016)
Chris J. Oates, Jim Q. Smith, Sach Mukherjee, James Cussens
Exact estimation of multiple directed acyclic graphs. Stat. Comput. 26 (4) (2016)
Chris J. Oates, Jim Q. Smith, Sach Mukherjee
Estimating Causal Structure Using Conditional DAG Models. J. Mach. Learn. Res. 17 (2016)
Chris J. Oates, Sach Mukherjee
Joint Structure Learning of Multiple Non-Exchangeable Networks. AISTATS (2014)
Chris J. Oates, Frank Dondelinger, Nora Bayani, James Korkola, Joe W. Gray, Sach Mukherjee
Causal network inference using biochemical kinetics. Bioinform. 30 (17) (2014)
Steven M. Hill, Sach Mukherjee
Network-based clustering with mixtures of L1-penalized Gaussian graphical models: an empirical investigation CoRR (2013)
Chris J. Oates, Bryan T. J. Hennessy, Yiling Lu, Gordon B. Mills, Sach Mukherjee
Network inference using steady-state data and Goldbeter-Koshland kinetics. Bioinform. 29 (6) (2013)
Chris J. Oates, Bryan T. J. Hennessy, Yiling Lu, Gordon B. Mills, Sach Mukherjee
Network inference using steady-state data and Goldbeter-koshland kinetics. Bioinform. 28 (18) (2012)
Steven M. Hill, Richard M. Neve, Nora Bayani, Wen-Lin Kuo, Safiyyah Ziyad, Paul T. Spellman, Joe W. Gray, Sach Mukherjee
Integrating biological knowledge into variable selection: an empirical Bayes approach with an application in cancer biology. BMC Bioinform. 13 (2012)
Steven M. Hill, Yiling Lu, Jennifer Molina, Laura Heiser, Paul T. Spellman, Terence P. Speed, Joe W. Gray, Gordon B. Mills, Sach Mukherjee
Bayesian Inference of Signaling Network Topology in a Cancer Cell Line. Bioinform. 28 (21) (2012)
Sach Mukherjee, Steven M. Hill
Network clustering: probing biological heterogeneity by sparse graphical models. Bioinform. 27 (7) (2011)
Steven J. Kiddle, Oliver P. F. Windram, Stuart McHattie, Andrew Meade, Jim Beynon, Vicky Buchanan-Wollaston, Katherine J. Denby, Sach Mukherjee
. Bioinform. 26 (3) (2010)
Daniel James Barker, Steven M. Hill, Sach Mukherjee
: A Tempering Algorithm for Large-Sample Network Inference. PRIB (2010)
Sach Mukherjee, Steven Pelech, Richard M. Neve, Wen-Lin Kuo, Safiyyah Ziyad, Paul T. Spellman, Joe W. Gray, Terence P. Speed
Sparse combinatorial inference with an application in cancer biology. Bioinform. 25 (2) (2009)
David Montaner, Joaquín Tárraga, Jaime Huerta-Cepas, Jordi Burguet-Castell, Juan M. Vaquerizas, Lucía Conde, Pablo Minguez, Javier Vera, Sach Mukherjee, Joan Valls, Miguel A. G. Pujana, Eva Alloza, Javier Herrero, Fátima Al-Shahrour, Joaquín Dopazo
Next station in microarray data analysis: GEPAS. Nucleic Acids Res. 34 (Web-Server-Issue) (2006)
Sach Mukherjee, Stephen J. Roberts, Mark J. van der Laan
Data-adaptive test statistics for microarray data. ECCB/JBI (2005)
Sach Mukherjee, Stephen J. Roberts
A Theoretical Analysis of the Selection of Differentially Expressed Genes. J. Bioinform. Comput. Biol. 3 (3) (2005)
Sach Mukherjee, Stephen J. Roberts
Probabilistic Consistency Analysis for Gene Selection. CSB (2004)
Sach Mukherjee, Stephen J. Roberts
A Theoretical Analysis of Gene Selection. CSB (2004)