Jesper Løve Hinrich

According to our database, Jesper Løve Hinrich authored at least 13 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2024

Probabilistic PARAFAC2.

Philip J. H. Jørgensen, Søren Føns Vind Nielsen, Jesper Løve Hinrich, Mikkel N. Schmidt, Kristoffer H. Madsen, Morten Mørup

Entropy, August, 2024

Probabilistic Block Term Decomposition for the Modeling of Higher Order Arrays.

Jesper Løve Hinrich, Morten Mørup

Comput. Sci. Eng., 2024

Non-negative Tensor Mixture Learning for Discrete Density Estimation.

Kazu Ghalamkari, Jesper Løve Hinrich, Morten Mørup

CoRR, 2024

2023

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

Jesper Løve Hinrich, Morten Mørup

CoRR, 2023

2022

PARAFAC2×N: Coupled Decomposition of Multi-modal Data with Drift in N Modes.

Michael D. Sorochan Armstrong, Jesper Løve Hinrich, A. Paulina de la Mata, James J. Harynuk

CoRR, 2022

2020

The probabilistic tensor decomposition toolbox.

Jesper Løve Hinrich, Kristoffer H. Madsen, Morten Mørup

Mach. Learn. Sci. Technol., 2020

2019

Probabilistic Tensor Train Decomposition.

Jesper Løve Hinrich, Morten Mørup

Proceedings of the 27th European Signal Processing Conference, 2019

2018

Variational Bayesian Partially observed non-Negative Tensor Factorization.

Jesper Løve Hinrich, Søren Føns Vind Nielsen, Kristoffer Hougaard Madsen, Morten Mørup

Proceedings of the 28th IEEE International Workshop on Machine Learning for Signal Processing, 2018

Probabilistic Sparse Non-negative Matrix Factorization.

Jesper Løve Hinrich, Morten Mørup

Proceedings of the Latent Variable Analysis and Signal Separation, 2018

2017

Scalable group level probabilistic sparse factor analysis.

Jesper Løve Hinrich, Søren Føns Vind Nielsen, Nicolai André Brogaard Riis, Casper T. Eriksen, Jacob Frosig, Marco D. F. Kristensen, Mikkel N. Schmidt, Kristoffer Hougaard Madsen, Morten Mørup

Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

2016

Archetypal Analysis for Modeling Multisubject fMRI Data.

Jesper Løve Hinrich, Sophia Elizabeth Bardenfleth, Rasmus Erbou Røge, Nathan William Churchill, Kristoffer Hougaard Madsen, Morten Mørup

IEEE J. Sel. Top. Signal Process., 2016

Variational group-PCA for intrinsic dimensionality determination in fMRI data.

Jesper Løve Hinrich, Søren Føns Vind Nielsen, Kristoffer Hougaard Madsen, Morten Mørup

Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2016

Sparse Probabilistic Parallel Factor Analysis for the Modeling of PET and Task-fMRI Data.

Vincent Beliveau, Georgios Papoutsakis, Jesper Løve Hinrich, Morten Mørup

Proceedings of the Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging, 2016