Machine Learning-Science and Technology

Scope & Guideline

Exploring the intersection of technology and human interaction.

Introduction

Welcome to your portal for understanding Machine Learning-Science and Technology, featuring guidelines for its aims and scope. Our guidelines cover trending and emerging topics, identifying the forefront of research. Additionally, we track declining topics, offering insights into areas experiencing reduced scholarly attention. Key highlights include highly cited topics and recently published papers, curated within these guidelines to assist you in navigating influential academic dialogues.
LanguageEnglish
ISSN-
PublisherIOP Publishing Ltd
Support Open AccessNo
Country-
Type-
Converge-
AbbreviationMACH LEARN-SCI TECHN / Mach. Learn.-Sci. Technol.
Frequency4 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressTEMPLE CIRCUS, TEMPLE WAY, BRISTOL BS1 6BE, ENGLAND

Aims and Scopes

The journal "Machine Learning-Science and Technology" focuses on the intersection of machine learning methodologies and their applications in various scientific and technological domains. It aims to advance the understanding and development of machine learning techniques while addressing complex challenges across multiple fields.
  1. Machine Learning Techniques and Algorithms:
    The journal emphasizes innovative machine learning algorithms, including deep learning, reinforcement learning, and probabilistic models, which are applied to scientific problems.
  2. Physics-Informed Machine Learning:
    A significant focus area is the integration of physical principles with machine learning to develop models that are not only data-driven but also respect underlying physical laws.
  3. Data-Driven Discovery:
    The journal promotes research that utilizes machine learning for data-driven discovery in fields such as materials science, biology, and particle physics, facilitating the extraction of meaningful insights from complex datasets.
  4. Applications in High Energy Physics:
    There is a strong emphasis on applications of machine learning in high energy physics, including event classification, anomaly detection, and simulations, reflecting the journal's commitment to addressing challenges in this domain.
  5. Interdisciplinary Approaches:
    The journal encourages interdisciplinary research that combines machine learning with other scientific disciplines, fostering collaboration and innovation across fields.
The journal has identified several emerging themes that reflect current trends in machine learning research, showcasing the dynamic nature of the field and its expanding applications.
  1. Quantum Machine Learning:
    There is a growing trend towards the application of machine learning techniques in quantum computing and quantum information science, indicating an increasing interest in harnessing these technologies for complex problem-solving.
  2. Generative Models and Simulation:
    Research on generative models, particularly in the context of simulating physical systems and enhancing data generation, has gained momentum, reflecting the demand for advanced modeling techniques.
  3. Explainable AI in Scientific Research:
    There is an emerging focus on explainable AI, with researchers seeking to enhance the interpretability of machine learning models, which is crucial for applications in sensitive fields like healthcare and physics.
  4. Integration of Multimodal Data:
    The trend of integrating multimodal data sources for comprehensive analysis is on the rise, reflecting the need for holistic approaches to complex scientific questions.
  5. Robustness and Uncertainty Quantification:
    Increasing emphasis on the robustness of machine learning models and uncertainty quantification indicates a shift towards ensuring reliability and accuracy in scientific applications.

Declining or Waning

As the landscape of machine learning and its applications evolves, certain themes have seen a decline in focus within the journal. These waning scopes reflect shifting interests in the research community or the maturation of previously emerging fields.
  1. Traditional Statistical Methods:
    There has been a noticeable decrease in publications that rely solely on traditional statistical methods without integration of machine learning techniques, as the field shifts towards more complex, data-driven approaches.
  2. Basic Machine Learning Applications:
    Research focusing on basic applications of machine learning in less complex scenarios has seen a decline, as the journal increasingly emphasizes advanced applications in high-stakes scientific areas.
  3. Simplicity in Model Design:
    There appears to be a waning interest in simplistic model designs that do not leverage the full capabilities of modern machine learning frameworks, with a preference for more sophisticated, hybrid approaches.

Similar Journals

International Journal of Intelligent Engineering Informatics

Unlocking Insights in Intelligent Engineering and Informatics.
Publisher: INDERSCIENCE ENTERPRISES LTDISSN: 1758-8715Frequency: 4 issues/year

International Journal of Intelligent Engineering Informatics, published by INDERSCIENCE ENTERPRISES LTD, stands at the forefront of research in the interdisciplinary domains of computer science, artificial intelligence, and human-computer interaction. With an ISSN of 1758-8715 and E-ISSN of 1758-8723, this journal serves as a vital resource for researchers and professionals seeking to explore the latest advancements in intelligent engineering and informatics techniques crucial for the evolution of modern technologies. Although currently not an open-access publication, it provides a necessary platform for disseminating high-quality research; its impact factor continues to grow, attracting a diverse readership interested in signal processing, software development, and computer vision. Covering innovative topics from 2022 to 2024, the journal is committed to fostering scholarly dialogue that paves the way for emerging trends and applications in the field, ensuring its relevance and significance in today's rapidly advancing technological landscape.

Inteligencia Artificial-Iberoamerical Journal of Artificial Intelligence

Connecting Minds Through Open Access Scholarship.
Publisher: ASOC ESPANOLA INTELIGENCIA ARTIFICIALISSN: 1137-3601Frequency: 2 issues/year

Inteligencia Artificial-Iberoamerican Journal of Artificial Intelligence, published by the ASOC ESPANOLA INTELIGENCIA ARTIFICIAL, serves as a pivotal platform for disseminating cutting-edge research in the burgeoning fields of artificial intelligence and software development. Established in 1997 as an Open Access journal, it ensures broad accessibility to its scholarly content, thus fostering collaboration and knowledge exchange amongst researchers, professionals, and students across the globe. Based in Valencia, Spain, the journal currently operates within a significant timeline spanning from 2004 to 2010 and 2012 to 2024, enabling continual contributions to the academic discourse. Although it holds a Q4 quartile ranking in both the Artificial Intelligence and Software categories and a notable yet competitive Scopus ranking among its peers, the journal remains committed to advancing the understanding and application of sophisticated AI methodologies. As it continues to embrace innovative research, this journal stands as a crucial reference point for those keenly navigating the complexities of artificial intelligence in a rapidly evolving digital landscape.

PeerJ Computer Science

Connecting Researchers with Groundbreaking Discoveries
Publisher: PEERJ INCISSN: Frequency: 1 issue/year

PeerJ Computer Science is a leading open access journal published by PEERJ INC, dedicated to the field of computer science. Since its inception in 2015, it has made significant strides in promoting scholarly communication and accessibility to cutting-edge research. With an impressive impact factor reflected by a Q1 ranking in the Computer Science (miscellaneous) category and a Scopus rank of 51 out of 232, this journal stands at the forefront of its field. The journal's open access model ensures that groundbreaking findings are readily available to researchers, professionals, and students alike, fostering collaboration and innovation in the ever-evolving landscape of computer science. As it continues to publish until 2024 and beyond, PeerJ Computer Science remains an essential resource for those seeking to stay ahead in their research and practice.

Frontiers in Robotics and AI

Leading the Charge in Robotics and Artificial Intelligence Exploration
Publisher: FRONTIERS MEDIA SAISSN: 2296-9144Frequency: 1 issue/year

Frontiers in Robotics and AI is a leading journal dedicated to the exploration and dissemination of groundbreaking research in the fields of robotics and artificial intelligence. Published by FRONTIERS MEDIA SA in Switzerland, it has established itself as a vital resource for academics, professionals, and students since its inception in 2014. With an impressive Open Access model, the journal ensures that high-quality research is accessible to a global audience, fostering collaboration and innovation. The journal is recognized for its distinguished impact in the academic community, achieving Q2 quartile rankings in both Artificial Intelligence and Computer Science Applications as of 2023. It currently holds a solid position in Scopus rankings, with a rank of #123 out of 350 in Artificial Intelligence and #223 out of 817 in Computer Science Applications, reflecting its robust contribution to these dynamic disciplines. The journal's scope encompasses a wide range of topics, including but not limited to autonomous systems, machine learning, and human-robot interaction, making it an essential platform for innovative ideas and advanced research.

Evolving Systems

Exploring the Dynamics of Adaptive Systems
Publisher: SPRINGER HEIDELBERGISSN: 1868-6478Frequency: 4 issues/year

Evolving Systems, an esteemed journal published by Springer Heidelberg, focuses on advancing the interdisciplinary field of evolving systems, encompassing areas such as computer science applications, control and optimization, control and systems engineering, and modeling and simulation. Since its inception in 2010, the journal has made significant contributions to the academic community, currently holding a commendable Q2 ranking across multiple categories for the year 2023. With an impactful focus on the dynamic behaviors of systems and their adaptive methodologies, Evolving Systems serves as a crucial platform for researchers, professionals, and students aiming to explore and expand the boundaries of system evolution. Despite being a subscription-based journal, it remains committed to fostering high-quality research dissemination and encourages submissions that push the envelope of knowledge in this rapidly developing field. The journal employs a rigorous peer-review process, ensuring the publication of cutting-edge research that meets the highest scholarly standards.

Data Science and Engineering

Transforming research into real-world impact.
Publisher: SPRINGERNATUREISSN: 2364-1185Frequency: 4 issues/year

Data Science and Engineering is a premier open access journal published by SPRINGERNATURE, dedicated to advancing the fields of data science, artificial intelligence, computational mechanics, and information systems. Since its inception in 2016, this journal has rapidly established itself as a leader in the academic community, boasting an impressive Q1 ranking in multiple computer science categories, including Artificial Intelligence, Software, and Information Systems. With a commitment to disseminating high-quality research, it caters to a diverse audience of researchers, professionals, and students eager to explore the intersection of data and technology. The journal's robust global reach, combined with its respected reputation, empowers authors to share their findings widely, facilitating breakthroughs and innovations across the digital landscape. Join the vibrant community of scholars contributing to this integral field of study, and stay informed with the latest research by accessing the journal freely online.

PROGRAMMING AND COMPUTER SOFTWARE

Unveiling Insights into Evolving Programming Techniques
Publisher: PLEIADES PUBLISHING INCISSN: 0361-7688Frequency: 6 issues/year

PROGRAMMING AND COMPUTER SOFTWARE is a distinguished journal committed to advancing the field of software development and programming methodologies. Published by PLEIADES PUBLISHING INC, this journal has been a valuable resource since its inception in 1978, reaching out to researchers, professionals, and students alike. With an emphasis on rigorous peer-reviewed articles, the journal holds a Q3 ranking in the realm of Software according to the latest 2023 Category Quartiles. Though it does not offer open access, the journal ensures that high-quality research is disseminated to its audience, providing insights into evolving programming techniques, software engineering challenges, and innovative solutions. With its convergence of years extending to 2024, PROGRAMMING AND COMPUTER SOFTWARE remains a pivotal publication, fostering a deeper understanding of the complexities in computer programming while supporting the broader software community.

JOURNAL OF MACHINE LEARNING RESEARCH

Cutting-edge Research for Tomorrow's Intelligent Systems
Publisher: MICROTOME PUBLISSN: 1532-4435Frequency: 1 issue/year

JOURNAL OF MACHINE LEARNING RESEARCH, published by MICROTOME PUBL, stands as a premier journal in the realms of Artificial Intelligence, Control and Systems Engineering, Software, and Statistics and Probability. With an impressive Q1 ranking across multiple categories and a prominent Scopus ranking that places it among the top journals in its field—ranked 1st in Mathematics and 20th in both Artificial Intelligence and Software—this journal serves as a vital resource for cutting-edge research and advancements in machine learning. Established in 2001, it has been committed to disseminating high-quality research findings and innovative methodologies, addressing the evolving challenges and opportunities in machine learning. Furthermore, the journal maintains a rigorous peer-review process, ensuring that only the most significant contributions are published. With open access options available and a strong user-friendly platform, it invites researchers, professionals, and students to engage deeply with the pioneering work in the field.

Machine Learning and Knowledge Extraction

Empowering Researchers with Open Access to Cutting-Edge Findings
Publisher: MDPIISSN: Frequency: 4 issues/year

Machine Learning and Knowledge Extraction, published by MDPI, is an esteemed Open Access journal that has been at the forefront of disseminating cutting-edge research since its inception in 2019. Based in Switzerland, this journal has established itself as a significant contributor to the fields of Artificial Intelligence and Engineering, currently ranking in the Q2 category in Artificial Intelligence and Q1 in Engineering (miscellaneous) for 2023. With a notable Scopus ranking, it holds the 35th position out of 204 in Engineering, placing it in the 83rd percentile, while it ranks 127th out of 350 in Computer Science, reaching the 63rd percentile. Machine Learning and Knowledge Extraction serves as a vital platform for researchers, professionals, and students alike, promoting insightful discussions, innovative methodologies, and profound discoveries in machine learning and data extraction techniques. The journal's open access model ensures that groundbreaking research is widely accessible, fostering collaboration and advancing knowledge across various disciplines.

International Journal of Cognitive Informatics and Natural Intelligence

Bridging Human and Artificial Intelligence
Publisher: IGI GLOBALISSN: 1557-3958Frequency: 4 issues/year

The International Journal of Cognitive Informatics and Natural Intelligence, published by IGI Global, is an essential resource for researchers and professionals exploring the intersections of cognitive informatics, artificial intelligence, and human-computer interaction. Since its establishment in 2007, this journal has focused on advancing the understanding of cognitive systems and their applications in natural intelligence, contributing significantly to the fields of software engineering and interface design. Operating out of the United States, the journal aims to disseminate high-quality research and innovative methodologies to foster interdisciplinary collaboration. Despite its current standing in Q4 quartiles for the fields of Artificial Intelligence, Human-Computer Interaction, and Software, it serves as a vital platform for emerging scholars and seasoned professionals alike seeking to explore new frontiers in cognitive technologies. While it does not provide direct open access, these publications are instrumental in shaping academic discourse, and contribute to ongoing advancements in how we understand and integrate cognitive science into practical applications.