activity
20222026
most citedExploring and Analyzing Wildland Fire Data Via Machine Learning Techniques

1 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG2026

Predicting Anemia Among Under-Five Children in Nepal Using Machine Learning and Deep Learning

Deepak Bastola, Pitambar Acharya, Dipak Dulal +2

Childhood anemia remains a major public health challenge in Nepal and is associated with impaired growth, cognition, and increased morbidity. Using World Health Organization hemogl…

cs.LG2025

Leveraging Advanced Machine Learning to Predict Turbulence Dynamics from Temperature Observations at an Experimental Prescribed Fire

Dipak Dulal, Joseph J. Charney, Michael R. Gallagher +3

This study explores the potential for predicting turbulent kinetic energy (TKE) from more readily acquired temperature data using temperature profiles and turbulence data collected…

math.NA2024

Modified Levenberg-Marquardt Algorithm For Tensor CP Decomposition in Image Compression

Ramin Goudarzi Karim, Dipak Dulal, Carmeliza Navasca

This paper explores a new version of the Levenberg-Marquardt algorithm used for Tensor Canonical Polyadic (CP) decomposition with an emphasis on image compression and reconstructio…

cs.LG2023★ 1 cited

Exploring and Analyzing Wildland Fire Data Via Machine Learning Techniques

Dipak Dulal, Joseph J. Charney, Michael Gallagher +2

This research project investigated the correlation between a 10 Hz time series of thermocouple temperatures and turbulent kinetic energy (TKE) computed from wind speeds collected f…

math.NA2022★ 1 cited

Covid-19 Analysis Using Tensor Methods

Dipak Dulal, Ramin Goudarzi Karim, Carmeliza Navasca

In this paper, we use tensor models to analyze Covid-19 pandemic data. First, we use tensor models, canonical polyadic and higher-order Tucker decompositions, to extract patterns o…