by instadatahelp | Sep 2, 2023 | AI Blogs
Knowledge Hypergraph Embedding Meets Relational Algebra Authors: Bahare Fatemi, Perouz Taslakian, David Vazquez, David Poole; Volume 24, Issue 105, Pages 1-34, 2023. Abstract Relational databases have been successful in data storage and rely on query languages for...
![Test-Time Adaptation for Point Cloud Registration Using Multitask Meta-Auxiliary Learning (arXiv:2308.16481v1 [cs.CV]) – Point-TTA](https://instadatanews.com/wp-content/uploads/2023/08/arxiv-logo-fb-1080x675.png)
by instadatahelp | Sep 2, 2023 | AI Blogs
Introducing Point-TTA, a new framework for point cloud registration (PCR) that enhances the performance and generalization of registration models. Despite the impressive progress made by learning-based methods, adapting to unknown testing environments remains a...
by instadatahelp | Sep 2, 2023 | AI Blogs
Factor Graph Neural Networks Zhen Zhang, Mohammed Haroon Dupty, Fan Wu, Javen Qinfeng Shi, Wee Sun Lee; 24(181):1−54, 2023. Abstract In recent years, Graph Neural Networks (GNNs) have gained significant popularity and have achieved remarkable success in various...
by instadatahelp | Sep 2, 2023 | AI Blogs
The study focuses on dynamic motion generation tasks, such as contact and collisions, where small changes in policy parameters can have a significant impact on the outcomes. For instance, in soccer, even a slight variation in the hitting position, applied force, or...
by instadatahelp | Sep 2, 2023 | AI Blogs
Risk Bounds for Positive-Unlabeled Learning Under the Selected At Random Assumption Olivier Coudray, Christine Keribin, Pascal Massart, Patrick Pamphile; 24(107):1−31, 2023. Abstract Positive-Unlabeled learning (PU learning) is a variant of semi-supervised binary...
by instadatahelp | Sep 2, 2023 | AI Blogs
Recently, there has been a growing interest in Cross-network node classification (CNNC) which involves classifying nodes in a target network with limited labels by leveraging knowledge from a source network with abundant labels. In order to tackle this problem, we...
