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Found 8 papers, 1 papers with code
Deep Cross-species Feature Learning for Animal Face Recognition via Residual Interspecies Equivariant Network
We present an animal facial feature fusion module to treat the features of the lower half face as additional information, which improves the proposed RiseNet performance.
LiGNN: Graph Neural Networks at LinkedIn
In this paper, we present LiGNN, a deployed large-scale Graph Neural Networks (GNNs) Framework.
A Novel Cross-Perturbation for Single Domain Generalization
Horizontally, it applies image-level and feature-level perturbations to enhance the diversity of the training data, mitigating the issue of limited diversity in single-source domains.
Density peak clustering using tensor network
We evaluate the performance of our algorithm on six synthetic data sets, four real world data sets, and three commonly used computer vision data sets.
A Machine Learning Approach for Recruitment Prediction in Clinical Trial Design
Significant advancements have been made in recent years to optimize patient recruitment for clinical trials, however, improved methods for patient recruitment prediction are needed to support trial site selection and to estimate appropriate enrollment timelines in the trial design stage.
A Dashboard for Mitigating the COVID-19 Misinfodemic
This paper describes the current milestones achieved in our ongoing project that aims to understand the surveillance of, impact of and intervention on COVID-19 misinfodemic on Twitter.
Tripartite Information Mining and Integration for Image Matting
Regarding the nature of image matting, most researches have focused on solutions for transition regions.
Quantum inspired K-means algorithm using matrix product states
Matrix product state has become the algorithm of choice when studying one-dimensional interacting quantum many-body systems, which demonstrates to be able to explore the most relevant portion of the exponentially large quantum Hilbert space and find accurate solutions.
Computational Physics Quantum Physics
