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https://openreview.net/forum?id=olZAWuGOUz HousE: Knowledge Graph Embedding with Householder Parameterization | OpenReview The effectiveness of knowledge graph embedding (KGE) largely depends on the ability to model intrinsic relation patterns and mapping properties. However,... knowledge graph embedding house parameterization openreview https://www.amazon.science/publications/pge-robust-product-graph-embedding-learning-for-error-detection PGE: Robust product graph embedding learning for error detection - Amazon Science Although product graphs (PGs) have gained increasing attention in recent years for their successful applications in product search and recommendations, the... graph embedding learning for error detection pge robust https://openreview.net/forum?id=RrHOg72CCI&referrer=%5Bthe%20profile%20of%20Seong%20Jin%20Ahn%5D(%2Fprofile%3Fid%3D~Seong_Jin_Ahn1) Bootstrapped Knowledge Graph Embedding based on Neighbor Expansion | OpenReview Most Knowledge Graph(KG) embedding models require negative sampling to learn the representations of KG by discriminating the differences between positive and... knowledge graph embedding based on bootstrapped neighbor expansion https://openreview.net/forum?id=P4W74BXoyBy Rot-Pro: Modeling Transitivity by Projection in Knowledge Graph Embedding | OpenReview Knowledge graph embedding models learn the representations of entities and relations in the knowledge graphs for predicting missing links (relations) between... knowledge graph embedding rot pro modeling transitivity https://openreview.net/forum?id=OoOpO0u4Xd InGram: Inductive Knowledge Graph Embedding via Relation Graphs | OpenReview Inductive knowledge graph completion has been considered as the task of predicting missing triplets between new entities that are not observed during training.... knowledge graph embedding ingram inductive via relation https://arxiv.org/abs/2506.03895 [2506.03895] Graph-Embedding Empowered Entity Retrieval Abstract page for arXiv paper 2506.03895: Graph-Embedding Empowered Entity Retrieval graph embedding 2506 03895 empowered entity https://arxiv.org/abs/1903.12287v1 [1903.12287v1] PyTorch-BigGraph: A Large-scale Graph Embedding System Abstract page for arXiv paper 1903.12287v1: PyTorch-BigGraph: A Large-scale Graph Embedding System a large graph embedding 1903 pytorch scale https://deepai.org/publication/chronor-rotation-based-temporal-knowledge-graph-embedding ChronoR: Rotation Based Temporal Knowledge Graph Embedding | DeepAI Mar 18, 2021 - 03/18/21 - Despite the importance and abundance of temporal knowledge graphs, most of the current research has been focused on reasoning on s... knowledge graph embedding rotation based temporal deepai https://arxiv.org/abs/2002.00819 [2002.00819] Knowledge Graph Embedding for Link Prediction: A Comparative Analysis Abstract page for arXiv paper 2002.00819: Knowledge Graph Embedding for Link Prediction: A Comparative Analysis knowledge graph embedding link prediction 2002 00819 https://openreview.net/forum?id=SoIwc1zg_TS&referrer=%5Bthe%20profile%20of%20David%20Poole%5D(%2Fprofile%3Fid%3D~David_Poole1) Improved Knowledge Graph Embedding Using Background Taxonomic Information. | OpenReview Knowledge graphs are used to represent relational information in terms of triples. To enable learning about domains, embedding models, such as tensor... knowledge graph embedding improved using background taxonomic https://aclanthology.org/N19-1099/ Integration of Knowledge Graph Embedding Into Topic Modeling with Hierarchical Dirichlet Process -... Dingcheng Li, Siamak Zamani, Jingyuan Zhang, Ping Li. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational... integration of knowledge graph embedding https://deepai.org/publication/pykg2vec-a-python-library-for-knowledge-graph-embedding Pykg2vec: A Python Library for Knowledge Graph Embedding | DeepAI Jun 4, 2019 - 06/04/19 - Pykg2vec is an open-source Python library for learning the representations of the entities and relations in knowledge graphs. Pykg... knowledge graph embedding python library deepai https://openreview.net/forum?id=7qvwMqs9Fz Learning Multi-interest Embedding with Dynamic Graph Cluster for Sequention Recommendation |... Multi-interest recommendation is to predict the next item by representing diversity of a user preference with multiple interest embeddings. Although existing... learning multi interest embedding https://openreview.net/forum?id=T7kquivfZC Tight and fast generalization error bound of graph embedding in metric space | OpenReview Recent studies have experimentally shown that we can achieve in non-Euclidean metric space effective and efficient graph embedding, which aims to obtain the... https://arxiv.org/abs/2401.06727v1 [2401.06727v1] Deep Manifold Graph Auto-Encoder for Attributed Graph Embedding Abstract page for arXiv paper 2401.06727v1: Deep Manifold Graph Auto-Encoder for Attributed Graph Embedding auto encoder 2401 deep manifold graph https://openreview.net/forum?id=pQzZPODLvQQ&referrer=%5Bthe%20profile%20of%20Brian%20Reily%5D(%2Fprofile%3Fid%3D~Brian_Reily1) Representing Multi-Robot Structure through Multimodal Graph Embedding for the Selection of Robot... Multi-robot systems of increasing size and complexity are used to solve large-scale problems, such as area exploration and search and rescue. A key decision in... https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2020.608512/full Frontiers | Hierarchical Microbial Functions Prediction by Graph Aggregated Embedding Matching 16S rRNA gene sequencing data to a metabolic reference database is a meaningful way to predict the metabolic function of bacteria and archaea, bring... frontiers hierarchical microbial functions prediction https://www.mdpi.com/1424-8220/22/7/2648 Word Embedding Distribution Propagation Graph Network for Few-Shot Learning Few-shot learning (FSL) is of great significance to the field of machine learning. The ability to learn and generalize using a small number of samples is an... word embedding propagation graph few shot distribution network https://arxiv.org/abs/2312.16834 [2312.16834] Hierarchical Aggregations for High-Dimensional Multiplex Graph Embedding Abstract page for arXiv paper 2312.16834: Hierarchical Aggregations for High-Dimensional Multiplex Graph Embedding high dimensional 2312 hierarchical aggregations multiplex https://www.amazon.science/publications/from-load-tests-to-live-streams-graph-embedding-based-anomaly-detection-in-microservice-architectures From load tests to live streams: Graph embedding-based anomaly detection in microservice... Prime Video regularly conducts load tests to simulate the viewer traffic spikes seen during live events such as Thursday Night Football as well as... https://aclanthology.org/2021.findings-acl.96/ OntoEA: Ontology-guided Entity Alignment via Joint Knowledge Graph Embedding - ACL Anthology Yuejia Xiang, Ziheng Zhang, Jiaoyan Chen, Xi Chen, Zhenxi Lin, Yefeng Zheng. Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021. 2021. knowledge graph embedding https://openreview.net/forum?id=r1lGO0EKDH GraphZoom: A Multi-level Spectral Approach for Accurate and Scalable Graph Embedding | OpenReview A multi-level spectral approach to improving the quality and scalability of unsupervised graph embedding. https://arxiv.org/abs/2311.12465 [2311.12465] Towards a Gateway for Knowledge Graph Schemas Collection, Analysis, and Embedding Abstract page for arXiv paper 2311.12465: Towards a Gateway for Knowledge Graph Schemas Collection, Analysis, and Embedding https://arxiv.org/abs/2508.02044 [2508.02044] Graph Unlearning via Embedding Reconstruction -- A Range-Null Space Decomposition... Abstract page for arXiv paper 2508.02044: Graph Unlearning via Embedding Reconstruction -- A Range-Null Space Decomposition Approach https://deepai.org/publication/a-comprehensive-study-on-knowledge-graph-embedding-over-relational-patterns-based-on-rule-learning A Comprehensive Study on Knowledge Graph Embedding over Relational Patterns Based on Rule Learning... Aug 15, 2023 - 08/15/23 - Knowledge Graph Embedding (KGE) has proven to be an effective approach to solving the Knowledge Graph Completion (KGC) task. Relat... knowledge graph embedding https://arxiv.org/abs/1905.08636 [1905.08636] Joint embedding of structure and features via graph convolutional networks Abstract page for arXiv paper 1905.08636: Joint embedding of structure and features via graph convolutional networks https://aclanthology.org/2020.coling-main.48/ RatE: Relation-Adaptive Translating Embedding for Knowledge Graph Completion - ACL Anthology Hao Huang, Guodong Long, Tao Shen, Jing Jiang, Chengqi Zhang. Proceedings of the 28th International Conference on Computational Linguistics. 2020. knowledge graph rate relation adaptive translating https://openreview.net/forum?id=8wGXnjRLSy Zero-shot Node Classification with Graph Contrastive Embedding Network | OpenReview This paper studies zero-shot node classification, which aims to predict new classes (i.e., unseen classes) of nodes in a graph. This problem is challenging yet... zero shot node classification graph contrastive https://neo4j.com/blog/tag/embedding/ embedding Archives - Graph Database & Analytics graph database embedding archives analytics