output
20122024
most citedLink Prediction via Generalized Coupled Tensor Factorisation

27 citations

5 papers

cs.LG2024★ 1 cited

PARAFAC2-based Coupled Matrix and Tensor Factorizations with Constraints

Carla Schenker, Xiulin Wang, David Horner +2

Data fusion models based on Coupled Matrix and Tensor Factorizations (CMTF) have been effective tools for joint analysis of data from multiple sources. While the vast majority of C…

cs.LG2024★ 4 cited

CORE-BEHRT: A Carefully Optimized and Rigorously Evaluated BEHRT

Mikkel Odgaard, Kiril Vadimovic Klein, Sanne Møller Thysen +3

The widespread adoption of Electronic Health Records (EHR) has significantly increased the amount of available healthcare data. This has allowed models inspired by Natural Language…

stat.ML2023★ 3 cited

Probabilistic Block Term Decomposition for the Modelling of Higher-Order Arrays

Jesper Løve Hinrich, Morten Mørup

Tensors are ubiquitous in science and engineering and tensor factorization approaches have become important tools for the characterization of higher order structure. Factorizations…

stat.CO2014★ 2 cited

Variational Inference For Probabilistic Latent Tensor Factorization with KL Divergence

Beyza Ermis, Y. Kenan Yılmaz, A. Taylan Cemgil +1

Probabilistic Latent Tensor Factorization (PLTF) is a recently proposed probabilistic framework for modelling multi-way data. Not only the common tensor factorization models but al…

cs.LG2012★ 27 cited

Link Prediction via Generalized Coupled Tensor Factorisation

Beyza Ermiş, Evrim Acar, A. Taylan Cemgil

This study deals with the missing link prediction problem: the problem of predicting the existence of missing connections between entities of interest. We address link prediction u…