2025-12-09-16_articles_updated
Published:
期刊: Nature Methods
标题: 破解癌症微生物组
英文标题: Cracking the cancer microbiome
链接: https://www.nature.com/articles/s41592-025-02953-3
期刊: Computational biology and bioinformatics : nature.com subject feeds
标题: 多维度组学整合机器学习框架识别巨噬细胞-成纤维细胞-肿瘤共浸润模式以预测胃癌预后
英文标题: Multi-dimensional omics integrated machine learning framework identifies macrophage-fibroblast-tumor co-infiltration patterns to predict prognosis in gastric cancer
链接: https://www.nature.com/articles/s41746-025-02179-9
期刊: Computational biology and bioinformatics : nature.com subject feeds
标题: 破解癌症微生物组
英文标题: Cracking the cancer microbiome
链接: https://www.nature.com/articles/s41592-025-02953-3
期刊: Computational biology and bioinformatics : nature.com subject feeds
标题: Mammo-AGE：基于深度学习的从乳腺X光片估算乳腺年龄
英文标题: Mammo-AGE: deep learning estimation of breast age from mammograms
链接: https://www.nature.com/articles/s41467-025-65923-5
期刊: Computational biology and bioinformatics : nature.com subject feeds
标题: 利用机器学习开发、验证和预后评估MASHRisk评分：多队列研究中的见解
英文标题: Harnessing machine learning for the development, validation, and prognostic evaluation of MASHRisk score: insights from a multicohort study
链接: https://www.nature.com/articles/s41746-025-02220-x
期刊: cs.LG updates on arXiv.org
标题: 通过多保真机器学习连接量子计算与经典计算以解决偏微分方程
英文标题: Bridging quantum and classical computing for partial differential equations through multifidelity machine learning
链接: https://arxiv.org/abs/2512.05241
期刊: cs.LG updates on arXiv.org
标题: 当忘记成本为零时：利用低影响力点来降低计算成本
英文标题: When unlearning is free: leveraging low influence points to reduce computational costs
链接: https://arxiv.org/abs/2512.05254
期刊: cs.LG updates on arXiv.org
标题: DMAGT：通过图转换模型整合SMILES和RNA序列结构揭示miRNA-药物关联
英文标题: DMAGT: Unveiling miRNA-Drug Associations by Integrating SMILES and RNA Sequence Structures through Graph Transformer Models
链接: https://arxiv.org/abs/2512.05287
期刊: cs.LG updates on arXiv.org
标题: 科学机器学习中使用稀疏变分高斯过程Kolmogorov-Arnold网络的不确定性量化
英文标题: Uncertainty Quantification for Scientific Machine Learning using Sparse Variational Gaussian Process Kolmogorov-Arnold Networks (SVGP KAN)
链接: https://arxiv.org/abs/2512.05306
期刊: cs.LG updates on arXiv.org
标题: 智能挖掘时间：用于比特币硬件投资回报率预测的深度学习框架
英文标题: Smart Timing for Mining: A Deep Learning Framework for Bitcoin Hardware ROI Prediction
链接: https://arxiv.org/abs/2512.05402
期刊: cs.LG updates on arXiv.org
标题: 如何通过集成学习平衡准确性和过拟合：从表格数据的偏差-方差角度分析
英文标题: How Ensemble Learning Balances Accuracy and Overfitting: A Bias-Variance Perspective on Tabular Data
链接: https://arxiv.org/abs/2512.05469
期刊: cs.LG updates on arXiv.org
标题: 利用可解释机器学习对太空用低挥发性润滑剂的计算设计
英文标题: Computational Design of Low-Volatility Lubricants for Space Using Interpretable Machine Learning
链接: https://arxiv.org/abs/2512.05870
期刊: cs.LG updates on arXiv.org
标题: 通过机器学习开发用于企业级商业调查的合成微数据
英文标题: Developing synthetic microdata through machine learning for firm-level business surveys
链接: https://arxiv.org/abs/2512.05948
期刊: cs.LG updates on arXiv.org
标题: PoolNet：用于2D到3D视频处理验证的深度学习
英文标题: PoolNet: Deep Learning for 2D to 3D Video Process Validation
链接: https://arxiv.org/abs/2512.05362
期刊: cs.LG updates on arXiv.org
标题: 模型网关：模型驱动的药物发现模型管理平台
英文标题: Model Gateway: Model Management Platform for Model-Driven Drug Discovery
链接: https://arxiv.org/abs/2512.05462
期刊: cs.LG updates on arXiv.org
标题: 数据增强深度学习在井下深度传感和现场验证中的应用
英文标题: Data-Augmented Deep Learning for Downhole Depth Sensing and Field Validation
链接: https://arxiv.org/abs/2511.00129