Search Results for author: Xiao Qin

Found 7 papers, 0 papers with code

OrthoReg: Improving Graph-regularized MLPs via Orthogonality Regularization

no code implementations31 Jan 2023 Hengrui Zhang, Shen Wang, Vassilis N. Ioannidis, Soji Adeshina, Jiani Zhang, Xiao Qin, Christos Faloutsos, Da Zheng, George Karypis, Philip S. Yu

Graph Neural Networks (GNNs) are currently dominating in modeling graph-structure data, while their high reliance on graph structure for inference significantly impedes them from widespread applications.

Node Classification

Detecting Temporal shape changes with the Euler Characteristic Transform

no code implementations21 Dec 2022 Lewis Marsh, Felix Y. Zhou, Xiao Qin, Xin Lu, Helen M. Byrne, Heather A. Harrington

Organoids are multi-cellular structures which are cultured in vitro from stem cells to resemble specific organs (e. g., brain, liver) in their three-dimensional composition.

Topological Data Analysis

Scaling Knowledge Graph Embedding Models

no code implementations8 Jan 2022 Nasrullah Sheikh, Xiao Qin, Berthold Reinwald, Chuan Lei

Developing scalable solutions for training Graph Neural Networks (GNNs) for link prediction tasks is challenging due to the high data dependencies which entail high computational cost and huge memory footprint.

Knowledge Graph Embedding Link Prediction

Medical Entity Disambiguation Using Graph Neural Networks

no code implementations3 Apr 2021 Alina Vretinaris, Chuan Lei, Vasilis Efthymiou, Xiao Qin, Fatma Özcan

Entity disambiguation (also referred to as entity linking) is considered as an essential task in unlocking the wealth of such medical KBs.

Decision Making Entity Disambiguation +1

Knowledge Graph Embedding using Graph Convolutional Networks with Relation-Aware Attention

no code implementations14 Feb 2021 Nasrullah Sheikh, Xiao Qin, Berthold Reinwald, Christoph Miksovic, Thomas Gschwind, Paolo Scotton

Knowledge graph embedding methods learn embeddings of entities and relations in a low dimensional space which can be used for various downstream machine learning tasks such as link prediction and entity matching.

Graph Attention Knowledge Graph Embedding +1

Relation-aware Graph Attention Model With Adaptive Self-adversarial Training

no code implementations14 Feb 2021 Xiao Qin, Nasrullah Sheikh, Berthold Reinwald, Lingfei Wu

Furthermore, the expressivity of the learned representation depends on the quality of negative samples used during training.

Entity Embeddings Graph Attention +1

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