Prakash Borpatra Gohain

Kungliga Tekniska högskolan

H-index: 5

Europe-Sweden

About Prakash Borpatra Gohain

Prakash Borpatra Gohain, With an exceptional h-index of 5 and a recent h-index of 5 (since 2020), a distinguished researcher at Kungliga Tekniska högskolan, specializes in the field of Sparse Signal Processing, Machine Learning, Statistical Modelling.

His recent articles reflect a diverse array of research interests and contributions to the field:

Model Selection in High-Dimensional Block-Sparse General Linear Regression

Robust Information Criterion for Model Selection in Sparse High-Dimensional Linear Regression Models

Neural greedy pursuit for feature selection

Scale-Invariant and consistent Bayesian information criterion for order selection in linear regression models

New improved criterion for model selection in sparse high-dimensional linear regression models

The Quest for Robust Model Selection Methods in Linear Regression

Statistical model-based evaluation of neural networks

Relative Cost Based Model Selection for Sparse High-Dimensional Linear Regression Models

Prakash Borpatra Gohain Information

University	Kungliga Tekniska högskolan
Position	Ph.D. Student
Citations(all)	70
Citations(since 2020)	67
Cited By	20
hIndex(all)	5
hIndex(since 2020)	5
i10Index(all)	2
i10Index(since 2020)	2
Email	Access Email
University Profile Page	Kungliga Tekniska högskolan
Google Scholar	View Google Scholar Profile