◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Md Akmol Masud

Queen's University

5 papers hereh-index 228 citations10 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author3

Across the 4 of 5 papers where every author was matched, so the position is known.

fields
  • cs.LG4
  • cs.CL1
affiliations
  • Queen's University
HomepageORCID 0009-0009-1894-9533

identity via Semantic Scholar / OpenAlex

activity
20242026
most citedLorentz-Equivariant Quantum Graph Neural Network for High-Energy Physics

6 citations · 7 across the 5 of their papers we have counts for

collaborators
Showing 2024Show all

3 papers · 1 filter

cs.LG2024

Quantum Rationale-Aware Graph Contrastive Learning for Jet Discrimination

Md Abrar Jahin, Md. Akmol Masud, M. F. Mridha +2

In high-energy physics, particle jet tagging plays a pivotal role in distinguishing quark from gluon jets using data from collider experiments. While graph-based deep learning meth…

cs.LG2024★ 6 cited

Lorentz-Equivariant Quantum Graph Neural Network for High-Energy Physics

Md Abrar Jahin, Md. Akmol Masud, Md Wahiduzzaman Suva +2

The rapid data surge from the high-luminosity Large Hadron Collider introduces critical computational challenges requiring novel approaches for efficient data processing in particl…

cs.LG2024★ 1 cited

KACQ-DCNN: Uncertainty-Aware Interpretable Kolmogorov-Arnold Classical-Quantum Dual-Channel Neural Network for Heart Disease Detection

Md Abrar Jahin, Md. Akmol Masud, M. F. Mridha +2

Heart failure is a leading cause of global mortality, necessitating improved diagnostic strategies. Classical machine learning models struggle with challenges such as high-dimensio…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.