Machine learning for condensed matter physics

E Bedolla, LC Padierna… - Journal of Physics …, 2020 - iopscience.iop.org
Condensed matter physics (CMP) seeks to understand the microscopic interactions of matter
at the quantum and atomistic levels, and describes how these interactions result in both …

Classical symmetries and the quantum approximate optimization algorithm

R Shaydulin, S Hadfield, T Hogg, I Safro - Quantum Information …, 2021 - Springer
We study the relationship between the Quantum Approximate Optimization Algorithm
(QAOA) and the underlying symmetries of the objective function to be optimized. Our …

Multilevel combinatorial optimization across quantum architectures

H Ushijima-Mwesigwa, R Shaydulin… - ACM Transactions on …, 2021 - dl.acm.org
Emerging quantum processors provide an opportunity to explore new approaches for
solving traditional problems in the post Moore's law supercomputing era. However, the …

Predicting ayurveda-based constituent balancing in human body using machine learning methods

V Madaan, A Goyal - IEEE Access, 2020 - ieeexplore.ieee.org
Human Body constitution (prakriti) defines what is in harmony with human nature and what
will cause to move out of balance and experience illness. Tridosha defines the three basic …

Spatio-temporal prediction of crimes using network analytic approach

SK Dash, I Safro… - 2018 IEEE International …, 2018 - ieeexplore.ieee.org
It is quite evident that majority of the population lives in urban area today than in any time of
the human history. This trend seems to increase in coming years. A study [5] says that nearly …

Landslides and flood multi-hazard assessment using machine learning techniques

AM Youssef, AM Mahdi, HR Pourghasemi - Bulletin of Engineering …, 2022 - Springer
Saudi Arabia is affected by various types of natural hazards that affect people's lives and
property. In this paper, the effects of landslides and floods in Wadi Dawqah in Bahah region …

[PDF][PDF] Estimation of reference evapotranspiration using machine learning models with limited data

A Ayaz, M Rajesh, SK Singh, S Rehana - AIMS Geosci, 2021 - pdfs.semanticscholar.org
Estimation of reference evapotranspiration using machine learning models with limited data
Page 1 Estimation of reference evapotranspiration using machine learning models with limited …

[PDF][PDF] Classical symmetries and QAOA

R Shaydulin, S Hadfield, T Hogg… - arXiv preprint arXiv …, 2020 - researchgate.net
We study the relationship between the Quantum Approximate Optimization Algorithm
(QAOA) and the underlying symmetries of the objective function to be optimized. Our …

Machine learning algorithms for big data mining processing: A review

L Djafri, Y Gafour - International Conference on Artificial Intelligence and …, 2021 - Springer
Big data mining is an excellent source of information and knowledge from systems to end
users. However, managing such amounts of data or knowledge requires automation, which …

Use of support vector machines with a parallel local search algorithm for data classification and feature selection

T Cura - Expert Systems with Applications, 2020 - Elsevier
Over the last decade, the number of studies on machine learning has significantly increased.
One of the most widely researched areas of machine learning is data classification. Most big …