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Hyperboloid Embeddings

HypE

49 papers tagged archive 2025-07-28

Introduced by Nurendra Choudhary et al. in Self-Supervised Hyperboloid Representations from Logical Queries over Knowledge Graphs

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

Hyperboloid Embeddings (HypE) is a novel self-supervised dynamic reasoning framework, that utilizes positive first-order existential queries on a KG to learn representations of its entities and relations as hyperboloids in a Poincaré ball. HypE models the positive first-order queries as geometrical translation (t), intersection (∩), and union (∪). For the problem of KG reasoning in real-world datasets, the proposed HypE model significantly outperforms the state-of-the art results. HypE is also applied to an anomaly detection task on a popular e-commerce website product taxonomy as well as hierarchically organized web articles and demonstrate significant performance improvements compared to existing baseline methods. Finally, HypE embeddings can also be visualized in a Poincaré ball to clearly interpret and comprehend the representation space.

PaperSource

Papers archive 2025-07-28

30 shown of 49, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

20 shown of 51 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Articles2
Autonomous Driving2
BIG-bench Machine Learning2
Anomaly Detection1
Attribute1
Autonomous Vehicles1
CPU1
Claim Verification1
Continual Learning1
DeepFake Detection1
Diversity1
Emotional Intelligence1
Evolutionary Algorithms1
Face Swapping1
Fairness1
GPU1
GSM8K1
Grounded language learning1
Information Retrieval1
Instruction Following1

Usage over time archive 2025-07-28

Papers per year tagged with HypE: 2020 to 2025, peak 14 14 0 2020: 1 paper 2020 2021: 6 papers 2021 2022: 8 papers 2022 2023: 14 papers 2023 2024: 10 papers 2024 2025: 10 papers 2025
Papers per year the archive tags with this method, by the paper's archive date (49 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Graph Embeddings

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