Self-Balancing, Memory Efficient, Dynamic Metric Space Data Maintenance, for Rapid Multi-Kernel Estimation
机构 * University of Texas at Austin(德克萨斯大学奥斯汀分校)
高校专区
机构 * University of Texas at Austin(德克萨斯大学奥斯汀分校)
机构 * Computational Interpretation Group, Laboratory of Seismology and Physics of the Earth’s Interior, School of Earth and Space Sciences, University of Science and Technology of China(中国科学技术大学地球和空间科学学院地球物理学与地球内部物理实验室) ; SLB ; Bureau of Economic Geology, Jackson School of Geosciences, The University of Texas at Austin(德克萨斯大学奥斯汀分校地质学院经济地质局) ; Georgia Institute of Technology(佐治亚理工学院)
机构 * The University of Texas at Austin(德克萨斯大学奥斯汀分校)
Journal ref Proc. IEEE/CVF Conf. Comput. Vis. Pattern Recognit. (CVPR) 2025
机构 * Salesforce AI Research(Salesforce AI研究院) ; University of Texas at Austin(德克萨斯大学奥斯汀分校)
Comments The conference version of this paper is published at ICLR 2025
机构 * Max Planck Institute for Intelligent Systems(马克斯·普朗克智能系统研究所) ; Meshcapade ; Carnegie Mellon University(卡内基梅隆大学) ; UT Austin(得克萨斯大学奥斯汀分校) ; University of Amsterdam(阿姆斯特丹大学)
Comments Accepted in CVPR'25. Project Page: https://pico.is.tue.mpg.de
机构 * Jet Propulsion Laboratory, California Institute of Technology(喷气推进实验室、加州理工学院) ; University of Texas at Austin(德克萨斯大学奥斯汀分校) ; Georgia Institute of Technology(佐治亚理工学院)
机构 * Stanford University(斯坦福大学) ; The University of Texas at Austin(德克萨斯大学奥斯汀分校)
Journal ref JAMIA, 2024
机构 * UT Austin(德克萨斯大学奥斯汀分校) ; University of Utah(犹他大学)
机构 * The University of Texas at Austin(德克萨斯大学奥斯汀分校) ; Princeton Language & Intelligence(普林斯顿语言与智能)
机构 * Institute for Analytical Sociology, Linköping University(分析社会研究所,利乐普大学) ; Department of Government, University of Texas at Austin(政府系,德克萨斯大学奥斯汀分校)
Comments To appear as: Sakamoto, Kazuki, Connor T. Jerzak, and Adel Daoud. "A Scoping Review of Earth Observation and Machine Learning for Causal Inference: Implications for the Geography of Poverty." In Geography of Poverty, edited by Ola Hall and Ibrahim Wahab. Edward Elgar Publishing (Cheltenham, UK), 2025
机构 * Department of Statistics and Data Sciences, University of Texas at Austin(统计与数据科学系,德克萨斯大学奥斯汀分校)
机构 * Chandra Family Department of Electrical and Computer Engineering, The University of Texas at Austin(德克萨斯大学奥斯汀分校电气与计算机工程系) ; Intel Corporation(英特尔公司)
Journal ref IEEE Asilomar, 2023
机构 * University of Washington(华盛顿大学) ; Apple(苹果公司) ; Toyota Research Institute(丰田研究院) ; UT Austin(得克萨斯大学) ; Tel Aviv University(特拉维夫大学) ; Columbia University(哥伦比亚大学) ; Stanford(斯坦福) ; UCLA(加州大学洛杉矶分校) ; JSC ; LAION ; AI2 ; TUM(慕尼黑技术大学) ; CMU(卡内基梅隆大学) ; Hebrew University(希伯来大学) ; SambaNova ; Cornell(康奈尔大学) ; USC(南加州大学) ; Harvard(哈佛大学) ; UCSB(加州大学圣塔芭芭拉分校) ; SynthLabs ; Contextual AI ; DatologyAI
Comments Project page: https://www.datacomp.ai/dclm/
机构 * Georgia Institute of Technology(佐治亚理工学院) ; University of Texas at Austin(德克萨斯大学奥斯汀分校)
Comments 15 pages, 4 figures, AIED 2025
机构 * Georgia Institute of Technology(佐治亚理工学院) ; The University of Southern California(南加州大学) ; Technische Universität München(慕尼黑技术大学) ; Google DeepMind(谷歌DeepMind) ; The AI Institute(人工智能研究所) ; The Institute for Human and Machine Cognition(人机认知研究所) ; Duke University(杜克大学) ; Kuwait University(科威特大学) ; Stanford University(斯坦福大学) ; CNRS-University of Montpellier(国家科学研究中心-蒙彼利埃大学) ; LIRMM CNRS-AIST Joint Robotics Laboratory(联合机器人实验室) ; Simon Fraser University(西蒙弗雷泽大学) ; The University of Texas at Austin(德克萨斯大学奥斯汀分校) ; NVIDIA(英伟达) ; Carnegie Mellon University(卡内基梅隆大学) ; Harbin Institute of Technology(哈尔滨工业大学)
机构 * Department of Mathematics, Virginia Tech(弗吉尼亚理工学院数学系) ; Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin(德克萨斯大学奥登工程与科学研究院) ; Amentum, Edwards Air Force Base(艾门敦,爱德华兹空军基地) ; Air Force Research Laboratory, Edwards Air Force Base(空军研究实验室,爱德华兹空军基地)
Comments 22 pages, 8 figures
Journal ref Computer Physics Communications 313 (2025) 109619
机构 * Neurint LLC ; The University of Texas at Austin(德克萨斯大学奥斯汀分校) ; T2S Solutions(T2S解决方案)
Comments 7 pages, 1 figure, 1 table
机构 * University of Texas at Austin(德克萨斯大学奥斯汀分校) ; UMass Amherst(马萨诸塞大学阿姆赫斯特分校) ; Meta AI
Comments ICLR 2025