Sach Mukherjee

42 papers A* 1A 2Journal 33Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Causal Cellular Context Transfer Learning (C3TL): An Efficient Architecture for Prediction of Unseen Perturbation Effects. CoRR Michael Scholkemper, Sach Mukherjee
2026	J	`jnl`	Evolving Afferent Architectures: Biologically-inspired Models for Damage-Avoidance Learning. CoRR Wolfgang Maass, Sabine Janzen, Prajvi Saxena, Sach Mukherjee
2026	J	`jnl`	Many Experiments, Few Repetitions, Unpaired Data, and Sparse Effects: Is Causal Inference Possible? CoRR Felix Schur, Niklas Pfister, Peng Ding, Sach Mukherjee, Jonas Peters
2025	J	`jnl`	Large Language Models for Zero-shot Inference of Causal Structures in Biology. CoRR Izzy Newsham, Luka Kovacevic, Richard Moulange, Nan Rosemary Ke, Sach Mukherjee
2024	A*	`conf`	Invariance-based Learning of Latent Dynamics. ICLR Kai Lagemann, Christian Lagemann, Sach Mukherjee
2024	J	`jnl`	Simulation-based Benchmarking for Causal Structure Learning in Gene Perturbation Experiments. CoRR Luka Kovacevic, Izzy Newsham, Sach Mukherjee, John Whittaker
2023	J	`jnl`	Deep learning of causal structures in high dimensions under data limitations. Nat. Mac. Intell. Kai Lagemann, Christian Lagemann, Bernd Taschler, Sach Mukherjee
2023	J	`jnl`	Improved baselines for causal structure learning on interventional data. Stat. Comput. Robin Richter, Shankar Bhamidi, Sach Mukherjee
2023	J	`jnl`	Learning Latent Dynamics via Invariant Decomposition and (Spatio-)Temporal Transformers. CoRR Kai Lagemann, Christian Lagemann, Sach Mukherjee
2023	J	`jnl`	Regularized Joint Mixture Models. J. Mach. Learn. Res. Konstantinos Perrakis, Thomas Lartigue, Frank Dondelinger, Sach Mukherjee
2022	J	`jnl`	Deep Learning of Causal Structures in High Dimensions. CoRR Kai Lagemann, Christian Lagemann, Bernd Taschler, Sach Mukherjee
2022	J	`jnl`	High-Dimensional Undirected Graphical Models for Arbitrary Mixed Data. CoRR Konstantin Göbler, Anne Miloschewski, Mathias Drton, Sach Mukherjee
2022	J	`jnl`	On unsupervised projections and second order signals. CoRR Thomas Lartigue, Sach Mukherjee
2022	J	`jnl`	Scalable Regularised Joint Mixture Models. CoRR Thomas Lartigue, Sach Mukherjee
2021	J	`jnl`	Deep recurrent optical flow learning for particle image velocimetry data. Nat. Mach. Intell. Christian Lagemann, Kai Lagemann, Sach Mukherjee, Wolfgang Schröder
2020	A	`conf`	Evaluation of Causal Structure Learning Algorithms via Risk Estimation. UAI Marco Eigenmann, Sach Mukherjee, Marloes H. Maathuis
2020	J	`jnl`	High-dimensional regression in practice: an empirical study of finite-sample prediction, variable selection and ranking. Stat. Comput. Fan Wang, Sach Mukherjee, Sylvia Richardson, Steven M. Hill
2019	J	`jnl`	Ancestral causal learning in high dimensions with a human genome-wide application. CoRR Umberto Noè, Bernd Taschler, Joachim Täger, Peter Heutink, Sach Mukherjee
2019	J	`jnl`	Causal Learning via Manifold Regularization. J. Mach. Learn. Res. Steven M. Hill, Chris J. Oates, Duncan A. J. Blythe, Sach Mukherjee
2019	J	`jnl`	Model-based clustering in very high dimensions via adaptive projections. CoRR Bernd Taschler, Frank Dondelinger, Sach Mukherjee
2018	—	`conf`	SCCA-Ref: Novel Sparse Canonical Correlation Analysis with Reference to Discover Independent Spatial Associations Between White Matter Hyperintensities and Atrophy. MLMI@MICCAI Gerard Sanroma, Loes Rutten-Jacobs, Valerie Lohner, Johanna Kramme, Sach Mukherjee, Martin Reuter, Tony Stöcker, Monique M. B. Breteler
2017	J	`jnl`	Molecular heterogeneity at the network level: high-dimensional testing, clustering and a TCGA case study. Bioinform. Nicolas Städler, Frank Dondelinger, Steven M. Hill, Rehan Akbani, Yiling Lu, Gordon B. Mills, Sach Mukherjee
2016	J	`jnl`	A Gibbs Sampler for Learning DAGs. J. Mach. Learn. Res. Robert J. B. Goudie, Sach Mukherjee
2016	J	`jnl`	Estimating Causal Structure Using Conditional DAG Models. J. Mach. Learn. Res. Chris J. Oates, Jim Q. Smith, Sach Mukherjee
2016	J	`jnl`	Exact estimation of multiple directed acyclic graphs. Stat. Comput. Chris J. Oates, Jim Q. Smith, Sach Mukherjee, James Cussens
2014	J	`jnl`	Causal network inference using biochemical kinetics. Bioinform. Chris J. Oates, Frank Dondelinger, Nora Bayani, James Korkola, Joe W. Gray, Sach Mukherjee
2014	A	`conf`	Joint Structure Learning of Multiple Non-Exchangeable Networks. AISTATS Chris J. Oates, Sach Mukherjee
2013	J	`jnl`	Network inference using steady-state data and Goldbeter-Koshland kinetics. Bioinform. Chris J. Oates, Bryan T. J. Hennessy, Yiling Lu, Gordon B. Mills, Sach Mukherjee
2013	J	`jnl`	Network-based clustering with mixtures of L1-penalized Gaussian graphical models: an empirical investigation CoRR Steven M. Hill, Sach Mukherjee
2012	J	`jnl`	Bayesian Inference of Signaling Network Topology in a Cancer Cell Line. Bioinform. Steven M. Hill, Yiling Lu, Jennifer Molina, Laura Heiser, Paul T. Spellman, Terence P. Speed, Joe W. Gray, Gordon B. Mills, Sach Mukherjee
2012	J	`jnl`	Integrating biological knowledge into variable selection: an empirical Bayes approach with an application in cancer biology. BMC Bioinform. Steven M. Hill, Richard M. Neve, Nora Bayani, Wen-Lin Kuo, Safiyyah Ziyad, Paul T. Spellman, Joe W. Gray, Sach Mukherjee
2012	J	`jnl`	Network inference using steady-state data and Goldbeter-koshland kinetics. Bioinform. Chris J. Oates, Bryan T. J. Hennessy, Yiling Lu, Gordon B. Mills, Sach Mukherjee
2011	J	`jnl`	Network clustering: probing biological heterogeneity by sparse graphical models. Bioinform. Sach Mukherjee, Steven M. Hill
2010	—	`conf`	MC PRIB Daniel James Barker, Steven M. Hill, Sach Mukherjee
2010	J	`jnl`	Temporal clustering by affinity propagation reveals transcriptional modules in Bioinform. Steven J. Kiddle, Oliver P. F. Windram, Stuart McHattie, Andrew Meade, Jim Beynon, Vicky Buchanan-Wollaston, Katherine J. Denby, Sach Mukherjee
2009	—	`ch.`	Multiple Hypothesis Testing for Data Mining. Encyclopedia of Data Warehousing and Mining Sach Mukherjee
2009	J	`jnl`	Sparse combinatorial inference with an application in cancer biology. Bioinform. Sach Mukherjee, Steven Pelech, Richard M. Neve, Wen-Lin Kuo, Safiyyah Ziyad, Paul T. Spellman, Joe W. Gray, Terence P. Speed
2006	J	`jnl`	Next station in microarray data analysis: GEPAS. Nucleic Acids Res. 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
2005	J	`jnl`	A Theoretical Analysis of the Selection of Differentially Expressed Genes. J. Bioinform. Comput. Biol. Sach Mukherjee, Stephen J. Roberts
2005	—	`conf`	Data-adaptive test statistics for microarray data. ECCB/JBI Sach Mukherjee, Stephen J. Roberts, Mark J. van der Laan
2004	—	`conf`	A Theoretical Analysis of Gene Selection. CSB Sach Mukherjee, Stephen J. Roberts
2004	—	`conf`	Probabilistic Consistency Analysis for Gene Selection. CSB Sach Mukherjee, Stephen J. Roberts