Search Results for author: Mojtaba Nayyeri

Found 16 papers, 3 papers with code

Geometric Algebra based Embeddings for Static and Temporal Knowledge Graph Completion

no code implementations18 Feb 2022 Chengjin Xu, Mojtaba Nayyeri, Yung-Yu Chen, Jens Lehmann

In this work, we strive to move beyond the complex or hypercomplex space for KGE and propose a novel geometric algebra based embedding approach, GeomE, which uses multivector representations and the geometric product to model entities and relations.

Knowledge Graph Completion Knowledge Graph Embeddings +2

Box Embeddings for the Description Logic EL++

1 code implementation24 Jan 2022 Bo Xiong, Nico Potyka, Trung-Kien Tran, Mojtaba Nayyeri, Steffen Staab

Recently, various methods for representation learning on Knowledge Bases (KBs) have been developed.

Knowledge Graph Embedding

Multiple Run Ensemble Learning with Low-Dimensional Knowledge Graph Embeddings

no code implementations11 Apr 2021 Chengjin Xu, Mojtaba Nayyeri, Sahar Vahdati, Jens Lehmann

For example, instead of training a model one time with a large embedding size of 1200, we repeat the training of the model 6 times in parallel with an embedding size of 200 and then combine the 6 separate models for testing while the overall numbers of adjustable parameters are same (6*200=1200) and the total memory footprint remains the same.

Ensemble Learning Knowledge Graph Completion +3

Knowledge Graph Embeddings in Geometric Algebras

no code implementations COLING 2020 Chengjin Xu, Mojtaba Nayyeri, Yung-Yu Chen, Jens Lehmann

Knowledge graph (KG) embedding aims at embedding entities and relations in a KG into a lowdimensional latent representation space.

Knowledge Graph Embeddings Knowledge Graphs +1

TeRo: A Time-aware Knowledge Graph Embedding via Temporal Rotation

2 code implementations COLING 2020 Chengjin Xu, Mojtaba Nayyeri, Fouad Alkhoury, Hamed Shariat Yazdi, Jens Lehmann

We show our proposed model overcomes the limitations of the existing KG embedding models and TKG embedding models and has the ability of learning and inferringvarious relation patterns over time.

Knowledge Graph Embedding Link Prediction

5* Knowledge Graph Embeddings with Projective Transformations

no code implementations8 Jun 2020 Mojtaba Nayyeri, Sahar Vahdati, Can Aykul, Jens Lehmann

Most of the embedding models designed in Euclidean geometry usually support a single transformation type - often translation or rotation, which is suitable for learning on graphs with small differences in neighboring subgraphs.

Knowledge Graph Completion Knowledge Graph Embedding +3

Temporal Knowledge Graph Embedding Model based on Additive Time Series Decomposition

1 code implementation18 Nov 2019 Chengjin Xu, Mojtaba Nayyeri, Fouad Alkhoury, Hamed Shariat Yazdi, Jens Lehmann

Moreover, considering the temporal uncertainty during the evolution of entity/relation representations over time, we map the representations of temporal KGs into the space of multi-dimensional Gaussian distributions.

Knowledge Graph Completion Knowledge Graph Embedding +2

Adaptive Margin Ranking Loss for Knowledge Graph Embeddings via a Correntropy Objective Function

no code implementations9 Jul 2019 Mojtaba Nayyeri, Xiaotian Zhou, Sahar Vahdati, Hamed Shariat Yazdi, Jens Lehmann

To tackle this problem, several loss functions have been proposed recently by adding upper bounds and lower bounds to the scores of positive and negative samples.

Knowledge Graph Embeddings Knowledge Graphs +2

Soft Marginal TransE for Scholarly Knowledge Graph Completion

no code implementations27 Apr 2019 Mojtaba Nayyeri, Sahar Vahdati, Jens Lehmann, Hamed Shariat Yazdi

In this work, the TransE embedding model is reconciled for a specific link prediction task on scholarly metadata.

Knowledge Graph Completion Link Prediction +1

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