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Pavlo O. Dral • The Journal of Physical Chemistry Letters
(2020)
As the quantum chemistry (QC) community embraces machine learning (ML), the number of new methods and applications based on the combination of QC and ML is surging. In this Perspective, a view of the current state of affairs in this new and...
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Open Access
DOI: https://doi.org/10.1021/acs.jpclett.9b03664
Konstantinos G. Liakos, Patrizia Busato, Dimitrios Moshou, Simon Pearson et al. • Sensors
(2018)
Machine learning has emerged with big data technologies and high-performance computing to create new opportunities for data intensive science in the multi-disciplinary agri-technologies domain. In this paper, we present a comprehensive revi...
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DOI: https://doi.org/10.3390/s18082674
PMC: 6111295
Pat Langley B, Herbert A. Simon • Communications of the ACM
(1995)
M achine learning is the study of computational methods for improving performance by mechanizing the acquisition of knowledge from experience. Expert performance requires much domain-specific knowledge, and knowledge engineering has produce...
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DOI: https://doi.org/10.1145/219717.219768
C. Roychoudhury, R. Kumar, C. He, W. Y. Y. Cheng et al. • Earth System Science Data
(2026)
We present MATCHA (Model for Atmospheric Transport and Chemistry in Asia), a 17-year (2003–2019) regional hydroclimate-chemical reanalysis for Asia (58–140° E, 4– 40° N) at 12 km resolution. MATCHA couples the Weather Research and Forecasti...
DOAJ
Open Access (DOAJ)
DOI: 10.5194/essd-18-5209-2026
Jafar Ahmad Abed Alzubi, Anand Nayyar, Akshi Kumar • Journal of Physics Conference Series
(2018)
The current SMAC (Social, Mobile, Analytic, Cloud) technology trend paves the way to a future in which intelligent machines, networked processes and big data are brought together. This virtual world has generated vast amount of data which i...
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DOI: https://doi.org/10.1088/1742-6596/1142/1/012012
Thorsten Wuest, Daniel Weimer, Christopher Irgens, Klaus‐Dieter Thoben • Production & Manufacturing Research
(2016)
The nature of manufacturing systems faces ever more complex, dynamic and at times even chaotic behaviors. In order to being able to satisfy the demand for high-quality products in an efficient manner, it is essential to utilize all means av...
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DOI: https://doi.org/10.1080/21693277.2016.1192517
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,...
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DOI: https://doi.org/10.1080/23746149.2020.1797528
Ethem Alpaydın (2016)
A concise overview of machine learning -- computer programs that learn from data -- which underlies applications that include recommendation systems, face recognition, and driverless cars....
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Jessica J. Vamathevan, Dominic A. Clark, Paul Czodrowski, Ian Dunham et al. • Nature Reviews Drug Discovery
(2019)
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Open Access
DOI: https://doi.org/10.1038/s41573-019-0024-5
PMC: 6552674
Cieslak M, Irfanoglu MO, Meisler SL, Salo T et al. • Developmental cognitive neuroscience
(2026)
PMC
PMC Public Access (View-Only)
DOI: 10.1016/j.dcn.2026.101838
PMC: PMC13734816
Juliana Aparecida Anochi, Vinícius Albuquerque de Almeida, Haroldo Fraga de Campos Velho • Remote Sensing
(2021)
Many natural disasters in South America are linked to meteorological phenomena. Therefore, forecasting and monitoring climatic events are fundamental issues for society and various sectors of the economy. In the last decades, machine learni...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs13132468
Stephen J. Goodswen, Joel Barratt, Paul J Kennedy, Alexa Kaufer et al. • FEMS Microbiology Reviews
(2021)
To understand the intricacies of microorganisms at the molecular level requires making sense of copious volumes of data such that it may now be humanly impossible to detect insightful data patterns without an artificial intelligence applica...
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DOI: https://doi.org/10.1093/femsre/fuab015
PMC: 8498514
Goëry Genty, Lauri Salmela, John M. Dudley, Daniel Brunner et al. • Nature Photonics
(2020)
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Open Access
DOI: https://doi.org/10.1038/s41566-020-00716-4
S. Mostafa Mousavi, Gregory C. Beroza • Annual Review of Earth and Planetary Sciences
(2022)
Machine learning (ML) is a collection of methods used to develop understanding and predictive capability by learning relationships embedded in data. ML methods are becoming the dominant approaches for many tasks in seismology. ML and data m...
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DOI: https://doi.org/10.1146/annurev-earth-071822-100323
Stanislav Mazurenko, Zbyněk Prokop, Jiřı́ Damborský • ACS Catalysis
(2019)
Abstract Enzyme engineering plays a central role in developing efficient biocatalysts for biotechnology, biomedicine, and life sciences. Apart from classical rational design and directed evolution approaches, machine learning methods have b...
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DOI: https://doi.org/10.1021/acscatal.9b04321
Rohan Bhardwaj, Ankita R. Nambiar, Debojyoti Dutta • IEEE Annual International Computer Software and Applications Conference (COMPSAC)
(2017)
In the past few years, there has been significant developments in how machine learning can be used in various industries and research. This paper discusses the potential of utilizing machine learning technologies in healthcare and outlines ...
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DOI: https://doi.org/10.1109/compsac.2017.164
Sridhar Chandrasekaran, Yao-Feng Chang, Firman Mangasa Simanjuntak • Nanomaterials
(2026)
The memristor has long been known as a nonvolatile memory technology alternative and has recently been explored for neuromorphic computing, owing to its capability to mimic the synaptic plasticity of the human brain. The architecture of a m...
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Open Access (DOAJ)
DOI: 10.3390/nano16030179
Nora Alhazmi, Rana Almazroa, Muhannad Alshehri, Saad Bin Shabib et al. • Journal of Orthodontic Science
(2026)
OBJECTIVES:
This study aimed to evaluate facial soft-tissue features in adults with skeletal Class I relationships using three-dimensional (3D) imaging and machine learning to identify sex-specific anthropometric patterns and provide refere...
DOAJ
Open Access (DOAJ)
DOI: 10.4103/jos.jos_111_25
Azim Keshavarzian Nodehi, Nasrollah Moghadam Charkari • Machine Learning with Applications
(2022)
Word Sense Disambiguation (WSD) is one of the earliest problems in natural language processing which aims to determine the correct sense of words in context. The semantic information provided by WSD systems is highly beneficial to many task...
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Open Access (DOAJ)
DOI: 10.1016/j.mlwa.2022.100369
Alberto Gil-Maciá, J. Enrique Sierra-García, Matilde Santos • Machine Learning with Applications
(2026)
Discrete reinforcement learning (RL) offers interpretability advantages compared to continuous reinforcement learning. Neural networks used in continuous RL behave like black boxes that do not show an obvious relationship between the system...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.mlwa.2026.100919