Causality-driven feature selection and domain adaptation for enhancing chemical foundation models in downstream tasks by Eduardo Soares, Victor Yukio Shirasuna, Emilio Vital Brazil, Karen Fiorella Aquino Gutierrez, Renato Cerqueira, Dmitry Zubarev, Kristin Schmidt, Daniel P Sanders

“…These models undergo a task-agnostic learning phase, characterized by pre-training on extensive unlabeled corpora followed by fine-tuning on specific downstream tasks. …”
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Improving CSCL Performance: A Quasiexperimental Study with Control and Intervention Groups Comparing Informative and Suggestive Feedback by Lanqin Zheng, Kaushal Kumar Bhagat, Miaolang Long, Nitesh Kumar Jha

“…The students in experimental Group 1 adopted knowledge graph-based suggestive feedback, the students in experimental Group 2 adopted automated informative feedback, and the students in the control group adopted traditional online collaborative learning without any feedback. …”
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An improve fraud detection framework via dynamic representations and adaptive frequency response filter by Juncheng Yang, Shuxia Li, Zijun Huang, Junhang Wu

“…Consequently, we introduce the Dynamic Pattern with Adaptive Filter Graph Learning framework for telecom fraud detection. …”
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Human Sensitivity to Community Structure Is Robust to Topological Variation by Elisabeth A. Karuza, Ari E. Kahn, Danielle S. Bassett

“…The extent to which behavioral signatures of learning are robust to changes in community size and number is the focus of the present work. …”
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Distributed computations for large-scale networked systems using belief propagation by Qianqian Cai, Zhaorong Zhang, Minyue Fu

“…This paper introduces several related distributed algorithms, generalised from the celebrated belief propagation algorithm for statistical learning. These algorithms are suitable for a class of computational problems in large-scale networked systems, ranging from average consensus, sensor fusion, distributed estimation, distributed optimisation, distributed control, and distributed learning. …”
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Feature-enriched hyperbolic network geometry by Roya Aliakbarisani, M. Ángeles Serrano, Marián Boguñá

“…Notably, node features are at the core of deep learning techniques, such as graph convolutional neural networks (GCNs), offering great utility in downstream tasks. …”
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Addressing Occupational Diseases; Integrating the Discipline at Danylo Halytsky Lviv National Medical University by Z. Bilous, N. Grechkivska, L. Kobak, N. Drobinska, M. Butynska

“…The number of academic hours allocated for practical classes has also undergone significant changes, as depicted in graph 2. The number of practical hours is calculated for one academic group. …”
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A Unified Approach to Image Recognition and Cryptography via Flexible Weak Inverse Property Quasigroups by Mohammad Mazyad Hazzazi, Muhammad Nadeem, Muhammad Kamran, Muhammad Arshad, Samuel Asefa Fufa

“…Nonassociative algebra presents multiple options for comprehending and dealing with difficulties in graph theory, artificial intelligence, and cryptography. …”
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A Dual-View Approach for Multistation Short-Term Passenger Flow Prediction in Bus Transit Systems by Gang Luo, Haoxuan Kuang, Dongran Zhang, Kunxiang Deng, Jun Li

“…Simultaneously, in addition to considering the adjacency graph, the similarity of all the stations of the entire transit network is also considered and uses multigraph convolution and graph fusion modules. …”
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Mathematical Models for Management Information Systems on Digital Platforms: from Resource Management to Demand Forecasting by Viktor Godliuk

“…The use of optimization methods, graph algorithms, forecasting, and machine learning to improve the efficiency of digital systems is investigated. …”
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GNN for LoRa Device Fingerprint Identification by Bojun Zhang

“…This paper presents a deep learning-based system for the classification and identification of LoRa signals. …”
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Spatio-Temporal AI Modeling for Urban Traffic Calibration: A SUMO-Based Approach by Pablo Manglano-Redondo, Alvaro Paricio-Garcia, Miguel A. Lopez-Carmona

“… Urban traffic management is a critical challenge in modern cities, necessitating innovative solutions to optimize traffic flow and reduce congestion. This research presents the development of an AI engine leveraging spatio-temporal learning techniques for urban traffic calibration. …”
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Towards Understanding the Analysis, Models, and Future Directions of Sports Social Networks by Zhongbo Bai, Xiaomei Bai

“…Finally, we present promising research directions in the rapidly growing field, including mining the genes of sports team success with multiview learning, evaluating the impact of sports team collaboration with motif-based graph networks, finding the best collaborative partners in a sports team with attention-aware graph networks, and finding the rising star for a sports team with attribute-based convolutional neural networks. …”
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SMILES all around: structure to SMILES conversion for transition metal complexes by Maria H. Rasmussen, Magnus Strandgaard, Julius Seumer, Laura K. Hemmingsen, Angelo Frei, David Balcells, Jan H. Jensen

“…We utilize these SMILES to make simple molecular fingerprint (FP) and graph-based representations of the molecules to be used in the context of machine learning. …”
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Development of Digital Training Twins in the Aircraft Maintenance Ecosystem by Igor Kabashkin

“…A modular orchestration engine incorporates reinforcement learning agents for policy refinement, federated learning for privacy-preserving skill analytics, and knowledge graph-based curriculum models for dependency management. …”
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Fibre tracing in biomedical images: An objective comparison between seven algorithms. by Youssef Arafat, Cristina Cuesta-Apausa, Esther Castellano, Constantino Carlos Reyes-Aldasoro

“…In biomedical applications, the analysis of traces of vasculature, nerves or fibres of the extracellular matrix can help characterise processes like angiogenesis or the effect of a certain treatment. This paper presents an objective comparison of six existing methodologies (Edge detection, CT Fire, Scale Space, Twombli, U-Net and Graph Based) and one novel approach called Trace Ridges to trace biomedical images with fibre-like structures. …”
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Association of Chronic Pain with Motor Symptom Severity in Parkinson’s Disease: An Exploratory Cross-Sectional Analysis by Niels Pacheco-Barrios, Vivian D. B. Gagliardi, Roberta R. Grudtner, Iloba Gabriel Njokanma, Ben Illigens, John D. Rolston, Felipe Fregni, Kevin Pacheco-Barrios

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Separating Repeating Fast Radio Bursts Using the Minimum Spanning Tree as an Unsupervised Methodology by C. R. García, Diego F. Torres, Jia-Ming Zhu-Ge, Bing Zhang

“…However, their classification into repeaters and nonrepeaters is challenging. Here, we present the application of the graph theory minimum spanning tree (MST) methodology as an unsupervised classifier of repeater and nonrepeater FRBs. …”
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Molecular property prediction in the ultra‐low data regime by Basem A. Eraqi, Dmitrii Khizbullin, Shashank S. Nagaraja, S. Mani Sarathy

“…Here, we present adaptive checkpointing with specialization (ACS), a training scheme for multi-task graph neural networks that mitigates detrimental inter-task interference while preserving the benefits of MTL. …”
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Vers une ontologie de domaine pour l’analyse des tissus anciens. Le projet Silknow et le cas du patrimoine soyeux européen by Marie Puren, Pierre Vernus

“…In this article, we present the Silknow project (Silk heritage in the knowledge society: from punched card to big data, deep learning and visual/tangible simulations, 2018-2021). …”
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