2025-12-23-21_articles_updated
Published:
期刊: Computational biology and bioinformatics : nature.com subject feeds
标题: Clair3-RNA：一种基于深度学习的小变异检测器，用于长读长RNA测序数据
英文标题: Clair3-RNA: a deep learning-based small variant caller for long-read RNA sequencing data
链接: https://www.nature.com/articles/s41467-025-67237-y
期刊: Computational biology and bioinformatics : nature.com subject feeds
标题: 开发和评估一个基于环境因素的院外心脏骤停预测机器学习模型
英文标题: Development and evaluation of a machine learning model predicting out-of-hospital cardiac arrest using environmental factors
链接: https://www.nature.com/articles/s41746-025-02235-4
期刊: npj Digital Medicine
标题: 基于深度学习的无对比增强鼻咽癌诊断MRI模型：一种端到端的钆剂免用解决方案
英文标题: Deep learning-based non-contrast MRI model for nasopharyngeal carcinoma diagnosis: an end-to-end gadolinium-free solution
链接: https://www.nature.com/articles/s41746-025-02247-0
期刊: npj Digital Medicine
标题: 开发和评估一种利用环境因素预测院外心脏骤停的机器学习模型
英文标题: Development and evaluation of a machine learning model predicting out-of-hospital cardiac arrest using environmental factors
链接: https://www.nature.com/articles/s41746-025-02235-4
期刊: npj Digital Medicine
标题: 前瞻性评估语音作为隐蔽肝性脑病的数字生物标志物
英文标题: Prospective evaluation of speech as a digital biomarker for covert hepatic encephalopathy
链接: https://www.nature.com/articles/s41746-025-02276-9
期刊: cs.LG updates on arXiv.org
标题: 基于物理信息的轻量级机器学习在多种气候条件下进行航空能见度预报
英文标题: Physics-Informed Lightweight Machine Learning for Aviation Visibility Nowcasting Across Multiple Climatic Regimes
链接: https://arxiv.org/abs/2512.16967
期刊: cs.LG updates on arXiv.org
标题: 电动汽车充电负荷预测：机器学习方法的实验比较
英文标题: Electric Vehicle Charging Load Forecasting: An Experimental Comparison of Machine Learning Methods
链接: https://arxiv.org/abs/2512.17257
期刊: cs.LG updates on arXiv.org
标题: 基于深度学习的Inconel 625代用蠕变模型：高温合金研究
英文标题: Deep Learning-Based Surrogate Creep Modelling in Inconel 625: A High-Temperature Alloy Study
链接: https://arxiv.org/abs/2512.17477
期刊: cs.LG updates on arXiv.org
标题: 机器学习在静态和单事件动态复杂网络分析中的应用
英文标题: Machine Learning for Static and Single-Event Dynamic Complex Network Analysis
链接: https://arxiv.org/abs/2512.17577
期刊: cs.LG updates on arXiv.org
标题: 利用Open Food Facts预测食品加工级别的机器学习应用
英文标题: Application of machine learning to predict food processing level using Open Food Facts
链接: https://arxiv.org/abs/2512.17169
期刊: cs.LG updates on arXiv.org
标题: 基于机器学习的波纹变换非晶态径向分布函数参数调优
英文标题: Machine Learning Assisted Parameter Tuning on Wavelet Transform Amorphous Radial Distribution Function
链接: https://arxiv.org/abs/2512.17245
期刊: cs.LG updates on arXiv.org
标题: LibriVAD：一个具有深度学习基准的 scalable open dataset 用于语音活动检测
英文标题: LibriVAD: A Scalable Open Dataset with Deep Learning Benchmarks for Voice Activity Detection
链接: https://arxiv.org/abs/2512.17281
期刊: cs.LG updates on arXiv.org
标题: MAD-OOD：一种基于深度学习、集群驱动的分布外恶意软件检测和分类框架
英文标题: MAD-OOD: A Deep Learning Cluster-Driven Framework for an Out-of-Distribution Malware Detection and Classification
链接: https://arxiv.org/abs/2512.17594
期刊: cs.LG updates on arXiv.org
标题: 机器学习可解释方法中的插补不确定性
英文标题: Imputation Uncertainty in Interpretable Machine Learning Methods
链接: https://arxiv.org/abs/2512.17689
期刊: cs.LG updates on arXiv.org
标题: 低秩滤波和光滑在序列深度学习中的应用
英文标题: Low-Rank Filtering and Smoothing for Sequential Deep Learning
链接: https://arxiv.org/abs/2410.06800
期刊: cs.LG updates on arXiv.org
标题: 数学副驾驶员的数据：展示机器学习证明的更好方法
英文标题: Data for Mathematical Copilots: Better Ways of Presenting Proofs for Machine Learning
链接: https://arxiv.org/abs/2412.15184
期刊: cs.LG updates on arXiv.org
标题: 一个用于射频指纹识别的通用机器学习框架
英文标题: A Generic Machine Learning Framework for Radio Frequency Fingerprinting
链接: https://arxiv.org/abs/2510.09775
期刊: cs.LG updates on arXiv.org
标题: 迈向预测过程挖掘的可重复性：SPICE — 一个深度学习库
英文标题: Towards Reproducibility in Predictive Process Mining: SPICE – A Deep Learning Library
链接: https://arxiv.org/abs/2512.16715
期刊: cs.LG updates on arXiv.org
标题: 机器学习驱动的复杂科学工作流程中的预测资源管理
英文标题: Machine Learning-Driven Predictive Resource Management in Complex Science Workflows
链接: https://arxiv.org/abs/2509.11512
期刊: cs.LG updates on arXiv.org
标题: 自动机器学习流程：大语言模型辅助的自动化数据集生成用于训练机器学习的原子间势
英文标题: Automated Machine Learning Pipeline: Large Language Models-Assisted Automated Dataset Generation for Training Machine-Learned Interatomic Potentials
链接: https://arxiv.org/abs/2509.21647
期刊: cs.LG updates on arXiv.org
标题: 机器学习训练流程的I/O性能预测建模：一种数据驱动的存储优化方法
英文标题: Predictive Modeling of I/O Performance for Machine Learning Training Pipelines: A Data-Driven Approach to Storage Optimization
链接: https://arxiv.org/abs/2512.06699