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Machine learning for quantum matter

Juan Carrasquilla • Advances in Physics X (2020)

Quantum matter, the research field studying phases of matter whose properties are intrinsically quantum mechanical, draws from areas as diverse as hard condensed matter physics, materials science, statistical mechanics, quantum information,...

OPENALEX cc-by DOI: https://doi.org/10.1080/23746149.2020.1797528

Interactive machine learning

Jerry Alan Fails, Dan R. Olsen • ACM International Conference on Intelligent User Interfaces (IUI) (2003)

Perceptual user interfaces (PUIs) are an important part of ubiquitous computing. Creating such interfaces is difficult because of the image and signal processing knowledge required for creating classifiers. We propose an interactive machine...

OPENALEX DOI: https://doi.org/10.1145/604045.604056

Machine learning and complex biological data

Chunming Xu, Scott A. Jackson • Genome biology (2019)

Machine learning has demonstrated potential in analyzing large, complex biological data. In practice, however, biological information is required in addition to machine learning for successful application....

OPENALEX cc-by DOI: https://doi.org/10.1186/s13059-019-1689-0 PMC: 6469083

Physics-Informed Machine Learning

Steven L. Brunton, J. Nathan Kutz • Cambridge University Press eBooks (2022)

Data-driven discovery is revolutionizing how we model, predict, and control complex systems. Now with Python and MATLAB®, this textbook trains mathematical scientists and engineers for the next generation of scientific discovery by offering...

OPENALEX DOI: https://doi.org/10.1017/9781009089517.019

Development of a Transfer Learning Technique for Rapid Adaptation of Thermal Compensation Models to Long-Term Machine Thermal Behavior Changes

Chia-Chin Chuang, Zheng-Wei Lin Chi, Tzu-Chien Kuo, Che-Jui Chang et al. • Machines (2026)

Structural aging and environmental changes associated with long-term operation can substantially modify the thermal behavior of machine tools, diminishing the accuracy of existing thermal compensation models. Traditional neural network appr...

DOAJ Open Access (DOAJ) DOI: 10.3390/machines14030309

Integrating InVEST and machine learning to model mangrove habitat degradation trend in in Northern Persian Gulf, Iran

Mohamad Kazemi, Atefeh Jafarpoor, Youssef Ahmadi, Raoof Mostafazadeh • Scientific Reports (2026)

Abstract The expansion of human activities and environmental changes in coastal desert and semi-desert ecosystems significantly impact habitat quality. This study used remote sensing data on the Google Earth Engine (GEE) platform to generat...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-47305-z

Towards a physics informed digital twin to predict cerebral blood flow and cerebral vascular regulation

Jennifer K. Briggs, J. N. Stroh, Soojin Park, Brandon Foreman et al. • npj Digital Medicine (2026)

Abstract Cerebral blood flow is essential for brain function and is governed by cerebral perfusion pressure and physiological mechanisms collectively referred to as cerebral vascular regulation (CVR). Direct measurement of cerebral blood fl...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41746-026-02600-x