Preface and Statement of Peer Review: 43rd International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt 2024) ^†

1. Introduction

The 43rd International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt 2024) took place at Ghent University in Ghent, Belgium, from 1 to 5 July 2024. As one of the oldest running conferences in the domain of data science, probability and, more recently, machine learning, over the years this series of workshops has seen an unusually broad range of applications in almost every domain of science, in particular physical science. Likewise, at the 43rd edition in Ghent, applications of Bayesian and maximum entropy methods were shown in thermodynamics, quantum mechanics, materials science, astronomy, fusion energy, economy, genetics, and many more fields. In keeping with another tradition of the workshop, several contributions focused on new data analysis methods, as well as the foundations of probability and physics. In addition, four tutorial talks and five invited talks were delivered.

The present volume contains a selection of papers based on work presented at the 43rd MaxEnt meeting.

2. Tutorial Speakers

• Romke Bontekoe (Bontekoe Research, The Netherlands): Bayesian Basics;
• Kevin Knuth (University at Albany—SUNY, USA): From Cox’s Foundation of Probability Theory to Physics;
• John Skilling (Maximum Entropy Data Consultants Ltd., Ireland): Computational Inference;
• Ali Mohammad-Djafari (Centre National de la Recherche Scientifique, France): Bayesian Inference and Physics-Informed Deep Neural Networks Methods for Inverse Problems.

3. Invited Speakers

• Gert De Cooman (Ghent University, Belgium): Conservative Probabilistic Inference in Quantum Mechanics;
• John Skilling (Maximum Entropy Data Consultants Ltd., Ireland): The Arithmetic of Maths and Physics;
• Julio M. Stern (University of São Paulo, Brazil): The E-Value and the Full Bayesian Significance Test: Logical Properties and Philosophical Consequences;
• Jan Aelterman (Ghent University, Belgium): Sensor Fusion Approaches in Automotive Perception;
• Tom Loredo (Cornell University, USA): Understanding Populations of Light Curves and Spectra: Bayesian Functional Data Analysis in Astronomy.

4. Sponsors

The MaxEnt 2024 conference received funding from the Research Foundation—Flanders (FWO) and MDPI AG.

5. Statement of Peer Review

In submitting conference proceedings to Physical Sciences Forum, the Volume Editors of the proceedings would like to certify to the publisher that all papers published in this volume have been subjected to peer review by the designated expert referees and were administered by the Volume Editor strictly following the policies announced on the conference website [1].

The whole process was supervised by the conference committee and the Volume Editor and adhered to the professional and scientific standards expected of a proceedings journal published by MDPI and complied with the peer review policy and guidelines of Physical Sciences Forum, which can be found at the following link: https://www.mdpi.com/journal/psf/instruction_for_conference_organizers. The review reports were checked and archived by the Editorial Office of Physical Sciences Forum.

• Type of peer review: single-blind;
• Conference submission management system: Easychair;
• Number of submissions received: 22;
• Number of submissions sent for review: 22;
• Number of submissions accepted: 18;
• Acceptance rate (number of submissions accepted/number of submissions received): 82%;
• Average number of reviews per paper: 1.3;
• Total number of distinct reviewers involved: 16.

6. Review Criteria and Process

Our approach to manuscript review follows a single-blind process. In this format, the authors’ identities are concealed from the reviewers, while the reviewers’ identities remain anonymous to the authors. This system is designed to minimize bias and encourage an impartial evaluation of the work.

Each submitted paper is carefully evaluated by experts in the relevant field. Reviewers assess the manuscript based on the following key criteria:

• Originality: The manuscript’s contribution to the existing body of knowledge is critically examined. Reviewers consider whether the research presents new insights, innovative approaches, or original data.
• Novelty of the Topic: The relevance and novelty of the research topic are key factors. Reviewers evaluate whether the topic addresses emerging trends or gaps in the field and if it has the potential to significantly advance knowledge in the area.
• Methodological Rigor: Reviewers scrutinize the research design, data collection, analysis methods, and overall methodology to ensure that the study is scientifically sound and replicable. They look for appropriate use of techniques, statistical validity, and transparency in the methods.
• Clarity of Presentation: The readability, structure, and logical flow of the manuscript are assessed. Reviewers provide feedback on the clarity of arguments, the quality of writing, and whether the results and conclusions are well supported by the data.
• Consistency with the Scope of the MaxEnt Workshop Series: Finally, reviewers assess whether the paper aligns with the themes and focus of the workshop. The manuscript should contribute to the overarching objectives of the workshop and resonate with its audience.

After the review process, the Editor makes a decision based on the reviewers’ comments, which may include revisions, acceptance, or rejection of the paper. Of the 22 papers received, 18 were accepted for publication in these proceedings. All revised papers were reviewed in their modified form before acceptance. This rigorous process ensures that only high-quality, impactful research is published in Physical Sciences Forum.