K
Kai Li
Researcher at Princeton University
Publications - 328
Citations - 76948
Kai Li is an academic researcher from Princeton University. The author has contributed to research in topics: Computer science & Cache. The author has an hindex of 76, co-authored 220 publications receiving 56127 citations. Previous affiliations of Kai Li include EMC Corporation & Baylor College of Medicine.
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Journal ArticleDOI
Multiprocessor cache coherence based on virtual memory support
Karin Petersen,Kai Li +1 more
TL;DR: It is shown that VM-based cache coherence performs well for scientific applications that require significant aggregate memory bandwidth and basically trades off design simplicity for increased software overheads.
Posted ContentDOI
NEURD: automated proofreading and feature extraction for connectomics
Brendan Celii,Stelios Papadopoulos,Zhuokun Ding,Paul G. Fahey,Eric Wang,Christos Papadopoulos,Alexander Kunin,Saumil S. Patel,J. Alexander Bae,Ágnes L. Bodor,Derrick Brittain,JoAnn Buchanan,Daniel J. Bumbarger,Manuel Castro,Erick Cobos,Sven Dorkenwald,Leila Elabbady,Akhilesh Halageri,Zhen Jia,Chris S. Jordan,D.J. Kapner,Nico Kemnitz,Sam Kinn,Kisuk Lee,Kai Li,Ran Lu,Thomas Macrina,Gayathri Mahalingam,Eric Mitchell,Shanka Subhra Mondal,Shang Mu,Barak Nehoran,Sergiy Popovych,Casey M Schneider-Mizell,William Silversmith,Marc Takeno,Russel Torres,Nicholas L. Turner,William Wong,Jingpeng Wu,Szi-chieh Yu,Wenjing Yin,Daniel Xenes,Lindsey Kitchell,Patricia K. Rivlin,Victoria A. Rose,Caitlyn Bishop,Brock A. Wester,Emmanouil Froudarakis,Edgar Y. Walker,Fabian H. Sinz,H. Sebastian Seung,Forrest Collman,Nuno Maçarico da Costa,R. Clay Reid,Xaq Pitkow,Andreas S. Tolias,Jake Reimer +57 more
TL;DR: NEURD as discussed by the authors is a software package that decomposes each meshed neuron into a compact and extensively-annotated graph representation, with these feature-rich graphs, they implement workflows for state of the art automated post-hoc proofreading of merge errors, cell classification, spine detection, axon-dendritic proximities, and other features that can enable many downstream analyses of neural morphology and connectivity.
Journal ArticleDOI
Recent progress in 3D printing degradable polylactic acid‐based bone repair scaffold for the application of cancellous bone defect
TL;DR: In this article , a series of biodegradable bone repair scaffolds based on polylactic acid composites and 3D printing technology are developed to achieve large bone defects, highlighting the relationship between materials, preparation methods, and applications.
Posted Content
Large Linear Multi-output Gaussian Process Learning for Time Series
TL;DR: In this paper, a large linear GP (LLGP) is proposed for multi-output GPs, which circumvents the need for stationarity by inducing structure in the LMC kernel through a common grid of inputs shared between outputs, enabling optimization of GP hyperparameters for multidimensional outputs and low-dimensional inputs.
Journal ArticleDOI
Exploratory Research on Key Technology of Human-Computer Interactive 2.5-Minute Fast Digital Early Warning for Mild Cognitive Impairment
Nan Li,Xiaotong Yang,Wencai Du,Atsushi Ogihara,Siyu Zhou,Xiaowen Ma,Yujia Wang,Shuwu Li,Kai Li +8 more
TL;DR: The experiment results show that the early warning technology, as a new generation of objective and effective digital early warning tool, can realize 2.5-minute fast and high-precision preliminary screening and early warning for MCI in the elderly.