Orthogonal Bases for Equivariant Graph Learning with Provable k-WL Expressive Power

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Research on cross-border enterprise knowledge sharing mechanism based on federated graph neural network and differential privacy collaboration

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Hybrid deep learning metaheuristic ensemble framework for enhanced COVID-19 classification using ResNet and particle swarm optimization

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Integrating gene expression and proteomics for breast cancer biomarker prediction through a deep learning framework with SHAP-based explainability

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Application of multimodal machine learning in building ecological assessment

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Self-efficacy and instructor support as determinants of ChatGPT effectiveness in student learning

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Design of an integrated federated large language models for semantic reasoning and self-organizing 6G networks

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Robustness and authorship bias of large language models in scientific abstracts scoring

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Bibliometric analysis of artificial intelligence application in bioinformatics

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Deep learning–based intelligent system for railway track monitoring and fault detection

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Artificial neural network optimized by Honey Badger Algorithm for predicting and explaining properties of 3D printed objects

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Optimal Experiment Design for Causal Effect Identification

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Context-aware transformer models for accounting-based inventory prediction and supply chain cost optimization

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Mean Aggregator is More Robust than Robust Aggregators under Label Poisoning Attacks on Distributed Heterogeneous Data

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The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond

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depyf: Open the Opaque Box of PyTorch Compiler for Machine Learning Researchers

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The ODE Method for Stochastic Approximation and Reinforcement Learning with Markovian Noise

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Improving Graph Neural Networks on Multi-node Tasks with the Labeling Trick

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Directed Cyclic Graphs for Simultaneous Discovery of Time-Lagged and Instantaneous Causality from Longitudinal Data Using Instrumental Variables

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Bayesian Sparse Gaussian Mixture Model for Clustering in High Dimensions

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