<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Navneet Singh and Shiva Raj Pokhrel | Deakin IoT &amp; Software Engineering Lab</title><link>https://deakiniotlab.au/author/navneet-singh-and-shiva-raj-pokhrel/</link><atom:link href="https://deakiniotlab.au/author/navneet-singh-and-shiva-raj-pokhrel/index.xml" rel="self" type="application/rss+xml"/><description>Navneet Singh and Shiva Raj Pokhrel</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Wed, 01 Jan 2025 00:00:00 +0000</lastBuildDate><image><url>https://deakiniotlab.au/media/icon_hu_428d647166466d7.png</url><title>Navneet Singh and Shiva Raj Pokhrel</title><link>https://deakiniotlab.au/author/navneet-singh-and-shiva-raj-pokhrel/</link></image><item><title>Modeling Quantum Machine Learning for Genomic Data Analysis</title><link>https://deakiniotlab.au/publication/shiva_raj_pokhrel/modeling_quantum_machine_learning_for_genomic_data/</link><pubDate>Wed, 01 Jan 2025 00:00:00 +0000</pubDate><guid>https://deakiniotlab.au/publication/shiva_raj_pokhrel/modeling_quantum_machine_learning_for_genomic_data/</guid><description/></item><item><title>An independent implementation of quantum machine learning algorithms in qiskit for genomic data</title><link>https://deakiniotlab.au/publication/shiva_raj_pokhrel/an_independent_implementation_of_quantum_machine_l/</link><pubDate>Fri, 01 Jan 2021 00:00:00 +0000</pubDate><guid>https://deakiniotlab.au/publication/shiva_raj_pokhrel/an_independent_implementation_of_quantum_machine_l/</guid><description/></item><item><title>Modeling Feature Maps for Quantum Machine Learning</title><link>https://deakiniotlab.au/publication/shiva_raj_pokhrel/modeling_feature_maps_for_quantum_machine_learning/</link><pubDate>Sat, 01 Jan 2011 00:00:00 +0000</pubDate><guid>https://deakiniotlab.au/publication/shiva_raj_pokhrel/modeling_feature_maps_for_quantum_machine_learning/</guid><description/></item></channel></rss>