机构

• 自动化研究所 [34]
• 计算技术研究所 [10]
• 沈阳自动化研究所 [4]
• 数学与系统科学研究院 [3]
• 成都山地灾害与环境研... [2]
• 上海药物研究所 [2]
• 更多

采集方式

• OAI收割 [60]
• iSwitch采集 [1]

内容类型

• 期刊论文 [57]
• 会议论文 [3]
• 学位论文 [1]

发表日期

• 2024 [12]
• 2023 [5]
• 2022 [22]
• 2021 [12]
• 2020 [2]
• 2019 [1]
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筛选

浏览/检索结果: 共61条，第1-10条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 MetaTKG plus plus : Learning evolving factor enhanced meta-knowledge for temporal knowledge graph reasoning 期刊论文  OAI收割 PATTERN RECOGNITION, 2024, 卷号: 155, 页码: 12 作者:  Xia, Yuwei;  Zhang, Mengqi;  Liu, Qiang;  Wang, Liang;  Wu, Shu   |  收藏  |  浏览/下载：11/0  |  提交时间：2024/09/09 Knowledge extraction  Temporal knowledge graph  Meta-learning  Evolution pattern   Learning to Sketch: A Neural Approach to Item Frequency Estimation in Streaming Data 期刊论文  OAI收割 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2024, 卷号: 46, 期号: 11, 页码: 7136-7153 作者:  Cao, Yukun;  Feng, Yuan;  Wang, Hairu;  Xie, Xike;  Zhou, S. Kevin   |  收藏  |  浏览/下载：10/0  |  提交时间：2024/12/06 sketches  meta-learning  Neural data structure  memory-augmented neural networks  memory-augmented neural networks  meta-learning  memory-augmented neural networks   Machine-Learning-Based Prediction Modeling for Debris Flow Occurrence: A Meta-Analysis 期刊论文  OAI收割 WATER, 2024, 卷号: 16, 期号: 7, 页码: 22 作者:  Yang, Lianbing;  Ge, Yonggang;  Chen, Baili;  Wu, Yuhong;  Fu, Runde   |  收藏  |  浏览/下载：27/0  |  提交时间：2024/05/20 machine learning  debris flow  occurrence  prediction  meta-analysis   Machine-Learning-Based Prediction Modeling for Debris Flow Occurrence: A Meta-Analysis 期刊论文  OAI收割 WATER, 2024, 卷号: 16, 期号: 7, 页码: 22 作者:  Yang, Lianbing;  Ge, Yonggang;  Chen, Baili;  Wu, Yuhong;  Fu, Runde   |  收藏  |  浏览/下载：17/0  |  提交时间：2024/05/15 machine learning  debris flow  occurrence  prediction  meta-analysis   Review on Peg-in-Hole Insertion Technology Based on Reinforcement Learning 会议论文  OAI收割 Chongqing, China, 2023-11 作者:  Shen Liancheng;  Su Jianhua;  Zhang Xiaodong   |  收藏  |  浏览/下载：15/0  |  提交时间：2024/06/24 —Robot Peg-in-hole Insertion  Reinforcement Learning  Meta-Reinforcement Learning   Meta-MolNet: A Cross-Domain Benchmark for Few Examples Drug Discovery 期刊论文  OAI收割 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2024, 页码: 15 作者:  Lv, Qiujie;  Chen, Guanxing;  Yang, Ziduo;  Zhong, Weihe;  Chen, Calvin Yu-Chian   |  收藏  |  浏览/下载：33/0  |  提交时间：2024/04/09 Benchmark platform  cross-domain meta-learning  drug discovery  few examples  Meta-MolNet  molecular property   Meta-MMFNet: Meta-learning-based Multi-model Fusion Network for Micro-expression Recognition 期刊论文  OAI收割 ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS, 2024, 卷号: 20, 期号: 2, 页码: 20 作者:  Gong, Wenjuan;  Zhang, Yue;  Wang, Wei;  Cheng, Peng;  Gonzalez, Jordi   |  收藏  |  浏览/下载：21/0  |  提交时间：2023/12/21 Feature fusion  model fusion  meta-learning  micro-expression recognition   Learning transferable cross-modality representations for few-shot hyperspectral and LiDAR collaborative classification 期刊论文  OAI收割 INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2024, 卷号: 126, 页码: 11 作者:  Dai, Mofan;  Xing, Shuai   |  收藏  |  浏览/下载：25/0  |  提交时间：2024/02/26 Multimodal remote sensing data  Meta-learning  Few-shot learning  Cross-modality feature learning   An effective global biochar application strategy for reducing global cropland nitrogen emissions without compromising crop yield: Findings from a global meta-analysis and density functional theory calculation 期刊论文  OAI收割 ENVIRONMENTAL TECHNOLOGY & INNOVATION, 2024, 卷号: 33, 页码: 17 作者:  He, Debo;  Dong, Zhixin;  Zhu, Bo   |  收藏  |  浏览/下载：28/0  |  提交时间：2024/07/08 Cropland N emissions  Meta-analysis  Biochar application  Machine-learning technology  Molecular model calculation   KinomeMETA: meta-learning enhanced kinome-wide polypharmacology profiling 期刊论文  OAI收割 BRIEFINGS IN BIOINFORMATICS, 2024, 卷号: 25, 期号: 1, 页码: 15 作者:  Ren, Qun;  Qu, Ning;  Sun, Jingjing;  Zhou, Jingyi;  Liu, Jin   |  收藏  |  浏览/下载：14/0  |  提交时间：2024/05/07 kinome profiling  kinase inhibitors  polypharmacology  deep learning  meta-learning