Jens Sjölund

Orcid: 0000-0002-9099-3522

According to our database1, Jens Sjölund authored at least 32 papers between 2014 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Ising on the Graph: Task-specific Graph Subsampling via the Ising Model.
CoRR, 2024

Entropy-regularized Diffusion Policy with Q-Ensembles for Offline Reinforcement Learning.
CoRR, 2024

2023
Learn2Reg: Comprehensive Multi-Task Medical Image Registration Challenge, Dataset and Evaluation in the Era of Deep Learning.
IEEE Trans. Medical Imaging, March, 2023

Probabilistic Estimation of Instantaneous Frequencies of Chirp Signals.
IEEE Trans. Signal Process., 2023

Variational Elliptical Processes.
CoRR, 2023

On Feynman-Kac training of partial Bayesian neural networks.
CoRR, 2023

Controlling Vision-Language Models for Universal Image Restoration.
CoRR, 2023

Privacy Amplification via Importance Sampling.
CoRR, 2023

Risk-sensitive Actor-free Policy via Convex Optimization.
CoRR, 2023

Neural incomplete factorization: learning preconditioners for the conjugate gradient method.
CoRR, 2023

Archetypal Analysis++: Rethinking the Initialization Strategy.
CoRR, 2023

A Tutorial on Parametric Variational Inference.
CoRR, 2023

Image Restoration with Mean-Reverting Stochastic Differential Equations.
Proceedings of the International Conference on Machine Learning, 2023

NTIRE 2023 Challenge on Stereo Image Super-Resolution: Methods and Results.
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Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

NTIRE 2023 Image Shadow Removal Challenge Report.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Refusion: Enabling Large-Size Realistic Image Restoration with Latent-Space Diffusion Models.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023



Risk-sensitive Actor-free Policy via Convex Optimisation.
Proceedings of the IJCAI-23 Joint Workshop on Artificial Intelligence Safety and Safe Reinforcement Learning (AISafety-SafeRL 2023) co-located with the 32nd International Joint Conference on Artificial Intelligence(IJCAI2023), 2023

2022
NUQ: A Noise Metric for Diffusion MRI via Uncertainty Discrepancy Quantification.
CoRR, 2022

Graph-based Neural Acceleration for Nonnegative Matrix Factorization.
CoRR, 2022

Private Learning Via Knowledge Transfer with High-Dimensional Targets.
Proceedings of the IEEE International Conference on Acoustics, 2022

Unsupervised dynamic modeling of medical image transformations.
Proceedings of the 25th International Conference on Information Fusion, 2022

2021
Latent linear dynamics in spatiotemporal medical data.
CoRR, 2021

2020
Decentralized Differentially Private Segmentation with PATE.
CoRR, 2020

Registration by tracking for sequential 2D MRI.
CoRR, 2020

The Elliptical Processes: a New Family of Flexible Stochastic Processes.
CoRR, 2020

Learning a Deformable Registration Pyramid.
Proceedings of the Segmentation, Classification, and Registration of Multi-modality Medical Imaging Data, 2020

2019
A unified representation network for segmentation with missing modalities.
CoRR, 2019

2018
Bayesian uncertainty quantification in linear models for diffusion MRI.
NeuroImage, 2018

2017
Gaussian process regression can turn non-uniform and undersampled diffusion MRI data into diffusion spectrum imaging.
Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017

2014
Skull Segmentation in MRI by a Support Vector Machine Combining Local and Global Features.
Proceedings of the 22nd International Conference on Pattern Recognition, 2014


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