Sumanta Basu
Sumanta Basu
Assistant Professor, Cornell University
Geverifieerd e-mailadres voor cornell.edu - Homepage
Geciteerd door
Geciteerd door
Regularized estimation in sparse high-dimensional time series models
S Basu, G Michailidis
The Annals of Statistics 43 (4), 1535-1567, 2015
Iterative random forests to discover predictive and stable high-order interactions
S Basu, K Kumbier, JB Brown, B Yu
Proceedings of the National Academy of Sciences 115 (8), 1943-1948, 2018
Sparse network modeling and metscape-based visualization methods for the analysis of large-scale metabolomics data
S Basu, W Duren, CR Evans, CF Burant, G Michailidis, A Karnovsky
Bioinformatics 33 (10), 1545-1553, 2017
Network granger causality with inherent grouping structure
S Basu, A Shojaie, G Michailidis
The Journal of Machine Learning Research 16 (1), 417-453, 2015
Metabolomic profiling identifies biochemical pathways associated with castration-resistant prostate cancer
AK Kaushik, SK Vareed, S Basu, V Putluri, N Putluri, K Panzitt, ...
Journal of proteome research 13 (2), 1088-1100, 2014
A debiased MDI feature importance measure for random forests
X Li, Y Wang, S Basu, K Kumbier, B Yu
arXiv preprint arXiv:1906.10845, 2019
Low rank and structured modeling of high-dimensional vector autoregressions
S Basu, X Li, G Michailidis
IEEE Transactions on Signal Processing 67 (5), 1207-1222, 2019
A system-wide approach to measure connectivity in the financial sector
S Basu, S Das, G Michailidis, AK Purnanandam
Adaptive thresholding for reconstructing regulatory networks from time-course gene expression data
A Shojaie, S Basu, G Michailidis
Statistics in Biosciences 4 (1), 66-83, 2012
High-Dimensional Estimation, Basis Assets, and the Adaptive Multi-Factor Model
L Zhu, S Basu, RA Jarrow, MT Wells
Quarterly Journal of Finance 10 (04), 2050017, 2020
Random forests for spatially dependent data
A Saha, S Basu, A Datta
Journal of the American Statistical Association, 1-19, 2021
Metabolic coessentiality mapping identifies C12orf49 as a regulator of SREBP processing and cholesterol metabolism
EC Bayraktar, K La, K Karpman, G Unlu, C Ozerdem, DJ Ritter, ...
Nature metabolism 2 (6), 487-498, 2020
Refining interaction search through signed iterative random forests
K Kumbier, S Basu, JB Brown, S Celniker, B Yu
arXiv preprint arXiv:1810.07287, 2018
Exploiting regulatory heterogeneity to systematically identify enhancers with high accuracy
H Arbel, S Basu, WW Fisher, AS Hammonds, KH Wan, S Park, ...
Proceedings of the National Academy of Sciences 116 (3), 900-908, 2019
Large spectral density matrix estimation by thresholding
Y Sun, Y Li, A Kuceyeski, S Basu
arXiv preprint arXiv:1812.00532, 2018
Methionine-homocysteine pathway in African-American prostate cancer
JH Gohlke, SM Lloyd, S Basu, V Putluri, SK Vareed, U Rasaily, ...
JNCI cancer spectrum 3 (2), pkz019, 2019
Sparse identification and estimation of large-scale vector autoregressive moving averages
I Wilms, S Basu, J Bien, DS Matteson
Journal of the American Statistical Association, 1-33, 2021
Dense time-course gene expression profiling of the Drosophila melanogaster innate immune response
F Schlamp, SYN Delbare, AM Early, MT Wells, S Basu, AG Clark
BMC genomics 22 (1), 1-22, 2021
Estimation in high-dimensional vector autoregressive models
S Basu, G Michailidis
arXiv preprint arXiv:1311.4175, 2013
Interpretable vector autoregressions with exogenous time series
I Wilms, S Basu, J Bien, DS Matteson
arXiv preprint arXiv:1711.03623, 2017
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