Information and Inference-A Journal of the IMA

Scope & Guideline

Connecting Scholars with Cutting-Edge Research

Introduction

Explore the comprehensive scope of Information and Inference-A Journal of the IMA through our detailed guidelines, including its aims and scope. Stay updated with trending and emerging topics, and delve into declining areas to understand shifts in academic interest. Our guidelines also showcase highly cited topics, featuring influential research making a significant impact. Additionally, discover the latest published papers and those with high citation counts, offering a snapshot of current scholarly conversations. Use these guidelines to explore Information and Inference-A Journal of the IMA in depth and align your research initiatives with current academic trends.
LanguageEnglish
ISSN2049-8764
PublisherOXFORD UNIV PRESS
Support Open AccessNo
Country-
Type-
Converge-
AbbreviationINF INFERENCE / Inf. Inference
Frequency4 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressGREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND

Aims and Scopes

The journal 'Information and Inference: A Journal of the IMA' focuses on the intersection of information theory and statistical inference, emphasizing rigorous mathematical frameworks and innovative methodologies. It serves as a platform for disseminating research that advances both theoretical and applied aspects of these fields.
  1. Statistical Inference and Learning:
    Research in this area includes theoretical advancements in statistical methods, machine learning algorithms, and inference techniques, particularly under high-dimensional settings.
  2. Graph Theory and Network Analysis:
    The journal publishes studies on graph-based models, network structures, and their applications in statistical inference, including topics like community detection and synchronization.
  3. Optimal Transport and Regularization Techniques:
    Papers often explore optimal transport theory, regularization methods, and their implications for recovery problems in various statistical contexts.
  4. Nonparametric and Robust Statistics:
    The journal emphasizes nonparametric methods and robust statistics, which are crucial for handling real-world data that may deviate from standard assumptions.
  5. High-Dimensional Statistics:
    A significant focus is placed on high-dimensional statistical methodologies, including concentration inequalities, minimax rates, and recovery guarantees in complex settings.
  6. Approximate Message Passing and Signal Processing:
    Research on algorithms for signal processing, including approximate message passing techniques and phase retrieval, is a prominent area of publication.
Recent publications in 'Information and Inference' reveal emerging themes that are gaining traction and reflect the current research landscape. This section outlines these trending areas of focus.
  1. Adversarial Robustness and Security:
    Research focusing on adversarial robustness has surged, reflecting the growing importance of security in statistical learning and machine learning applications.
  2. Deep Learning and Neural Networks:
    There is an increasing trend towards incorporating deep learning techniques, particularly in the context of statistical inference and high-dimensional data analysis.
  3. Statistical Learning Theory and Generalization:
    Papers addressing the theoretical underpinnings of statistical learning, including generalization bounds and error rates, are becoming more prevalent.
  4. Graph-based Learning and Analysis:
    The emergence of graph-based methodologies for data analysis, including spectral methods and graph neural networks, is increasingly represented in recent publications.
  5. Dynamic and Adaptive Algorithms:
    There is a growing interest in dynamic and adaptive algorithms that can respond to changing data environments, particularly in online learning contexts.

Declining or Waning

While certain themes remain robust, others appear to be losing prominence in the journal's recent publications. This section highlights those declining areas, reflecting shifts in research focus.
  1. Traditional Machine Learning Methods:
    There has been a noticeable decline in the publication of papers focused on classical machine learning models, as the field shifts towards more complex and high-dimensional approaches.
  2. Basic Statistical Models:
    Papers centered on foundational statistical models without high-dimensional or complex adaptations have become less frequent, indicating a move towards more sophisticated methodologies.
  3. Deterministic Algorithms for Optimization Problems:
    There seems to be a waning interest in purely deterministic approaches to optimization, with a shift towards stochastic and adaptive methods that can better handle uncertainty.

Similar Journals

Foundations and Trends in Communications and Information Theory

Pioneering Insights for a Connected Future
Publisher: NOW PUBLISHERS INCISSN: 1567-2190Frequency: 4 issues/year

Foundations and Trends in Communications and Information Theory, published by NOW PUBLISHERS INC, is a prestigious journal that has established itself as a leading platform in the fields of communications and information theory since its inception in 2004. With an impressive duration of publication extending to 2024, this journal captures the latest advancements and methodologies in applied mathematics, as well as computer networks and communications, currently ranking in the Q1 category in both domains for 2023. The journal's commitment to high-quality, peer-reviewed content is reflected in its significant impact factors, including a rank of #29 out of 635 in applied mathematics and #70 out of 395 in computer networks and communications on Scopus. By offering an in-depth look at theoretical underpinnings and practical applications, Foundations and Trends in Communications and Information Theory serves as an invaluable resource for researchers, professionals, and students alike, fostering innovation and scientific discourse in these rapidly evolving fields.

Journal of the Indian Society for Probability and Statistics

Promoting Excellence in Statistical Research and Application
Publisher: SPRINGERNATUREISSN: Frequency: 2 issues/year

Journal of the Indian Society for Probability and Statistics, published by SpringerNature in Germany, is a prominent platform dedicated to advancing the field of statistics and probability. With its E-ISSN of 2364-9569, the journal features rigorous research articles, reviews, and theoretical advancements aimed at promoting the application of statistical methodologies in diverse areas. As part of the academic community since 2016, it has maintained a commendable Q3 ranking in the Statistics and Probability category for 2023, indicating its growing influence and relevance. As the journal aims to foster collaborations among statisticians and probabilists, it serves as an invaluable resource for researchers, professionals, and students looking to deepen their understanding and share innovative ideas. While the journal operates under a subscription model, its commitment to open access publication contributes to the broader dissemination of knowledge in this vital field, further enhancing its importance and utility within the scientific landscape.

BIOMETRIKA

Exploring the Intersection of Theory and Application
Publisher: OXFORD UNIV PRESSISSN: 0006-3444Frequency: 4 issues/year

BIOMETRIKA, published by the esteemed Oxford University Press, stands as a pivotal journal in the fields of statistics, probability, and applied mathematics since its inception in 1908. With ISSN number 0006-3444 and E-ISSN 1464-3510, this journal maintains an impressive reputation, consistently achieving Q1 rankings across multiple categories including Agricultural and Biological Sciences, Applied Mathematics, and Statistics. Addressed to a global audience from its base in Oxford, United Kingdom, BIOMETRIKA serves as an essential platform for disseminating rigorous research aimed at advancing statistical methodologies and their applications. While the journal does not offer Open Access options, it is recognized for its high-impact output, holding significant positions in Scopus rankings - specifically attaining a 94th percentile rank in General Mathematics and a 91st percentile in Statistics and Probability. Scholars, professionals, and students alike will find in BIOMETRIKA a wealth of knowledge that bridges theory and practice within the vast domain of statistical science, making it indispensable for ongoing research and education in the field.

STATISTICA SINICA

Advancing the Frontiers of Statistical Science
Publisher: STATISTICA SINICAISSN: 1017-0405Frequency: 4 issues/year

STATISTICA SINICA, published by the esteemed STATISTICA SINICA organization, stands as a premier journal in the fields of Statistics and Probability, boasting a significant impact within the academic community. With an ISSN of 1017-0405 and E-ISSN of 1996-8507, this journal has evolved from its inception in 1996, continuing to publish cutting-edge research through 2024. As recognized by its recent categorization in Q1 quartiles in both Statistics and Probability and Statistics, Probability and Uncertainty for 2023, it ranks among the top journals in its discipline, meriting attention from researchers and practitioners alike. Despite lacking open access options, it delivers rigorous, peer-reviewed articles that contribute to the advancement of statistical science. With its base in Taiwan, and a dedicated editorial team located at the Institute of Statistical Science, Academia Sinica, Taipei, STATISTICA SINICA continues to be a vital resource for statisticians, data scientists, and related professionals seeking innovative methodologies and insights within this dynamic field.

STATISTICS & PROBABILITY LETTERS

Elevating the discourse in statistics and probability.
Publisher: ELSEVIERISSN: 0167-7152Frequency: 12 issues/year

STATISTICS & PROBABILITY LETTERS is a distinguished journal published by ELSEVIER, dedicated to advancing the field of statistics and probability. With an ISSN of 0167-7152 and an E-ISSN of 1879-2103, this journal is an essential platform for research, featuring cutting-edge studies and significant findings in the realms of statistical theory and applied probability. The journal operates under a notable Q3 ranking in both the categories of Statistics and Probability, and Statistics, Probability and Uncertainty for 2023, underscoring its relevance in these fields. Researchers, professionals, and students alike benefit from its rigorous peer-review process and its commitment to published integrity, fostering innovative insights from 1982 through its anticipated convergence in 2025. While it does not offer open access, the journal’s widely recognized impact within the academic community makes it a valuable resource for anyone seeking to deepen their understanding of statistical methodologies and probabilistic models.

BERNOULLI

Advancing the Frontiers of Statistical Knowledge
Publisher: INT STATISTICAL INSTISSN: 1350-7265Frequency: 4 issues/year

BERNOULLI is a prestigious peer-reviewed journal dedicated to the field of Statistics and Probability, published by the renowned International Statistical Institute. Since its inception in 1995, this journal has established itself as a vital resource for researchers and professionals, achieving a remarkable impact factor and consistently ranking in the top quartile (Q1) of its category as of 2023. With a strong presence in the Scopus database, where it ranks #64 among 278 journals in Mathematics, it places in the 76th percentile, underscoring its significance in the academic landscape. Although not an open-access journal, its contributions are pivotal for advancing statistical theory and its applications across various disciplines. As Berounlli continues to evolve until 2024, it remains committed to disseminating high-quality research that fosters innovation and supports the global analytics community. The journal’s scope encompasses a wide range of topics in statistics, including but not limited to theoretical statistics, applied statistics, and data analysis, making it an essential read for anyone engaged in statistical research.

Statistica

Empowering Researchers with Cutting-Edge Insights
Publisher: UNIV STUDI BOLOGNA, DIPT SCIENZE STATISTICHE PAOLO FORTUNATIISSN: 0390-590XFrequency: 4 issues/year

Statistica, an esteemed journal published by the Università degli Studi di Bologna, Dipartimento di Scienze Statistiche Paolo Fortunati, is a vital resource within the fields of statistical science and applied mathematics. Since its inception in 1969, this open-access journal has served as a platform for original research and comprehensive reviews, facilitating the dissemination of knowledge to a global audience. As of 2023, it is indexed in Scopus, holding a noteworthy position in the 43rd percentile in the realm of Decision Sciences and Statistics. Researchers and practitioners benefit from its focus on contemporary statistical methods, data analysis, and probability theory. With a commitment to fostering academic dialogue and collaboration, Statistica aims to highlight innovative findings and applications, ensuring that the community remains at the forefront of statistical advancements.

STATISTICS AND COMPUTING

Unlocking the power of data with expert statistical insights.
Publisher: SPRINGERISSN: 0960-3174Frequency: 1 issue/year

Statistics and Computing is a premier journal published by Springer, dedicated to advancing the fields of statistics and computational theory. With a strong focus on interdisciplinary research, this journal covers a broad spectrum of topics including, but not limited to, statistical methodologies, computational algorithms, and the latest advancements in data analysis. As of 2023, it proudly holds a Q1 ranking in multiple categories including Computational Theory and Mathematics and Statistics and Probability, underscoring its significant influence and recognition within the academic community. The journal's impact is further demonstrated by its commendable positions in Scopus ranks, making it a valuable resource for researchers, professionals, and students alike. Published in the Netherlands, Statistics and Computing is known for its rigorous peer-review process and commitment to quality, ensuring that only the most impactful research is disseminated to the global audience. Submissions from a diverse range of backgrounds are encouraged, fostering an inclusive environment for innovation and collaboration in the statistics and computing realm.

Journal of Statistical Planning and Inference

Exploring the Frontiers of Statistical Inference
Publisher: ELSEVIERISSN: 0378-3758Frequency: 12 issues/year

The Journal of Statistical Planning and Inference, published by ELSEVIER, stands as a significant platform within the fields of applied mathematics and statistics. With a history of rigorous scholarship since its inception in 1977, this journal provides a vital forum for researchers to share their advancements in statistical methodologies, planning, and inference techniques. As of 2023, it holds a respectable impact factor reflected in its Q2 rankings across multiple categories, including Applied Mathematics and Statistics and Probability, showcasing its influence and relevance in academic discourse. The journal is indexed in Scopus, with commendable rankings that affirm its scholarly merit, making it vital for professionals and students seeking the latest developments and research trends in statistical sciences. With a commitment to high-quality publications aimed at fostering innovation and practical solutions in statistical applications, the Journal of Statistical Planning and Inference is essential for anyone involved in empirical research and data-driven decision-making.

Sao Paulo Journal of Mathematical Sciences

Empowering researchers to share transformative mathematical insights.
Publisher: SPRINGER INT PUBL AGISSN: 1982-6907Frequency: 2 issues/year

Welcome to the Sao Paulo Journal of Mathematical Sciences, a pivotal platform dedicated to advancing the field of mathematics, published by Springer International Publishing AG. Established in 2015 and running until 2024, this journal serves as a vital resource for researchers, professionals, and students interested in a plethora of mathematical topics, including computational theory, statistics, and general mathematics. While the journal holds a current Q4 quartile ranking in its categories, it provides an opportunity for contributors to disseminate innovative findings in an accessible manner. Although not an open-access publication, the journal is committed to ensuring that high-quality research is available to the academic community, fostering collaboration and growth within the discipline. Researchers seeking to publish in a dynamic and developing journal should consider the Sao Paulo Journal of Mathematical Sciences as an essential avenue for their work.