Image Classification in High-Energy Physics: A Comprehensive Survey of Applications to Jet Analysis
Nowadays, there has been a growing trend in the fields of high-energy physics (HEP) in its
both parts experimental and phenomenological studies, to incorporate machine learning …
both parts experimental and phenomenological studies, to incorporate machine learning …
Machine learning-based remission prediction in rheumatoid arthritis patients treated with biologic disease-modifying anti-rheumatic drugs: findings from the Kuwait …
AR Alsaber, A Al-Herz, B Alawadhi, IA Doush… - Frontiers in Big …, 2024 - frontiersin.org
Background Rheumatoid arthritis (RA) is a common condition treated with biological disease-
modifying anti-rheumatic medicines (bDMARDs). However, many patients exhibit resistance …
modifying anti-rheumatic medicines (bDMARDs). However, many patients exhibit resistance …
High-resolution global ultrafine particle concentrations through a machine learning model and Earth observations
Atmospheric pollution is a major concern due to its well-documented and detrimental
impacts on human health, with millions of excess deaths attributed to it annually. Particulate …
impacts on human health, with millions of excess deaths attributed to it annually. Particulate …
Mixture-of-Experts Graph Transformers for Interpretable Particle Collision Detection
D Genovese, A Sgroi, A Devoto, S Valentine… - arXiv preprint arXiv …, 2025 - arxiv.org
The Large Hadron Collider at CERN produces immense volumes of complex data from high-
energy particle collisions, demanding sophisticated analytical techniques for effective …
energy particle collisions, demanding sophisticated analytical techniques for effective …
Analysis of Parameterized Quantum Circuits: on The Connection Between Expressibility and Types of Quantum Gates
Y Liu, K Baba, K Kaneko, N Takeda, J Koyama… - arXiv preprint arXiv …, 2024 - arxiv.org
Expressibility is a crucial factor of a Parameterized Quantum Circuit (PQC). In the context of
Variational Quantum Algorithms (VQA) based Quantum Machine Learning (QML), a QML …
Variational Quantum Algorithms (VQA) based Quantum Machine Learning (QML), a QML …
[PDF][PDF] Applications of artificial intelligence in materials research for fuel cells
H Liu, H Guo, Z Gao, H Pan, J Zheng, J Linghu… - AI & …, 2025 - pdf.elspublishing.com
The increasing global energy demand and the growing environmental problems have
intensified the pursuit of clean and sustainable energy solutions. Hydrogen, with its high …
intensified the pursuit of clean and sustainable energy solutions. Hydrogen, with its high …
A Simple Transfer Learning Approach for Assessing Small Datasets in Electrochemical Energy Cells Manufacturing
F Fernandez, S Saravanan, RL Omongos, JF Troncoso… - 2024 - chemrxiv.org
The performance of electrochemical cells for energy storage and conversion, such as
batteries and fuel cells, can be improved by optimizing their manufacturing processes. This …
batteries and fuel cells, can be improved by optimizing their manufacturing processes. This …
Use of SHAP for Interpreting a Drone ClassificationModel Based on Statistical Radar Features
S Raja, SK Das, YS Gan, KH Teo - 2023 IEEE 5th International …, 2023 - ieeexplore.ieee.org
The aim of this paper is to interpret a Light Gradient Boost-based model developed for
generic radar classification problems. Light gradient boosting machine (LGBM) being a …
generic radar classification problems. Light gradient boosting machine (LGBM) being a …