Data-driven discovery of statistically relevant information in quantum simulators
Quantum simulators offer powerful means to investigate strongly correlated quantum matter.
However, interpreting measurement outcomes in such systems poses significant challenges …
However, interpreting measurement outcomes in such systems poses significant challenges …
Anomalous fractal scaling in two-dimensional electric networks
Much of the qualitative nature of physical systems can be predicted from the way it scales
with system size. Contrary to the continuum expectation, we observe a profound deviation …
with system size. Contrary to the continuum expectation, we observe a profound deviation …
Temporal feature extraction and machine learning for classification of sleep stages using telemetry polysomnography
U Lal, S Mathavu Vasanthsena, A Hoblidar - Brain Sciences, 2023 - mdpi.com
Accurate sleep stage detection is crucial for diagnosing sleep disorders and tailoring
treatment plans. Polysomnography (PSG) is considered the gold standard for sleep …
treatment plans. Polysomnography (PSG) is considered the gold standard for sleep …
A Comparative Study on Feature Extraction Techniques for the Discrimination of Frontotemporal Dementia and Alzheimer's Disease with Electroencephalography in …
Early-stage Alzheimer's disease (AD) and frontotemporal dementia (FTD) share similar
symptoms, complicating their diagnosis and the development of specific treatment …
symptoms, complicating their diagnosis and the development of specific treatment …
A Novel Approach to Decision-Making on Diagnosing Oncological Diseases Using Machine Learning Classifiers Based on Datasets Combining Known and/or New …
LA Demidova - Mathematics, 2023 - mdpi.com
This paper deals with the problem of diagnosing oncological diseases based on blood
protein markers. The goal of the study is to develop a novel approach in decision-making on …
protein markers. The goal of the study is to develop a novel approach in decision-making on …
Data-driven discovery of relevant information in quantum simulators
Quantum simulators offer powerful means to investigate strongly correlated quantum matter.
However, interpreting measurement outcomes in such systems poses significant challenges …
However, interpreting measurement outcomes in such systems poses significant challenges …
Decision-Making on the Diagnosis of Oncological Diseases Using Cost-Sensitive SVM Classifiers Based on Datasets with a Variety of Features of Different Natures
LA Demidova - Mathematics, 2024 - mdpi.com
This paper discusses the problem of detecting cancer using such biomarkers as blood
protein markers. The purpose of this research is to propose an approach for making …
protein markers. The purpose of this research is to propose an approach for making …
Non-parametric learning critical behavior in Ising partition functions: PCA entropy and intrinsic dimension
We provide and critically analyze a framework to learn critical behavior in classical partition
functions through the application of non-parametric methods to data sets of thermal …
functions through the application of non-parametric methods to data sets of thermal …
Entropy Measures in Fractals for Sensing through Turbulent Environments
Fractal-structured beams offer non-line-of-sight sensing, self-similar statistics that
redundantly encode information, and robustness to turbulence. We will summarize our …
redundantly encode information, and robustness to turbulence. We will summarize our …
[PDF][PDF] Non-parametric learning in many-body physics.
RK Panda - 2023 - iris.sissa.it
In this digital age, machine learning (a prominent element within the context of artificial
intelligence) has become an integral part of modern life, influencing various aspects of our …
intelligence) has become an integral part of modern life, influencing various aspects of our …