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Rebecka Jörnsten
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2020 – today
- 2024
- [i8]Ziming Wang, Rebecka Jörnsten:
SE(3)-bi-equivariant Transformers for Point Cloud Assembly. CoRR abs/2407.09167 (2024) - 2023
- [j8]David Martínez-Enguita
, Sanjiv K. Dwivedi, Rebecka Jörnsten, Mika Gustafsson:
NCAE: data-driven representations using a deep network-coherent DNA methylation autoencoder identify robust disease and risk factor signatures. Briefings Bioinform. 24(5) (2023) - [i7]Viktor Andersson, Balázs Varga, Vincent Szolnoky, Andreas Syrén, Rebecka Jörnsten, Balázs Kulcsár:
Controlled Descent Training. CoRR abs/2303.09216 (2023) - [i6]Oskar Allerbo, Rebecka Jörnsten:
Solving Kernel Ridge Regression with Gradient-Based Optimization Methods. CoRR abs/2306.16838 (2023) - 2022
- [j7]Oskar Allerbo
, Rebecka Jörnsten:
Flexible, non-parametric modeling using regularized neural networks. Comput. Stat. 37(4): 2029-2047 (2022) - [c3]Vincent Szolnoky, Viktor Andersson, Balázs Kulcsár, Rebecka Jörnsten:
On the Interpretability of Regularisation for Neural Networks Through Model Gradient Similarity. NeurIPS 2022 - [i5]Oskar Allerbo, Rebecka Jörnsten:
Bandwidth Selection for Gaussian Kernel Ridge Regression via Jacobian Control. CoRR abs/2205.11956 (2022) - [i4]Vincent Szolnoky, Viktor Andersson, Balázs Kulcsár, Rebecka Jörnsten:
On the Interpretability of Regularisation for Neural Networks Through Model Gradient Similarity. CoRR abs/2205.12642 (2022) - 2021
- [j6]Oskar Allerbo, Rebecka Jörnsten:
Non-linear, Sparse Dimensionality Reduction via Path Lasso Penalized Autoencoders. J. Mach. Learn. Res. 22: 283:1-283:28 (2021) - [i3]Oskar Allerbo, Rebecka Jörnsten:
Non-linear, Sparse Dimensionality Reduction via Path Lasso Penalized Autoencoders. CoRR abs/2102.10873 (2021) - [i2]Olof Zetterqvist, Rebecka Jörnsten, Johan Jonasson:
Robust Neural Network Classification via Double Regularization. CoRR abs/2112.08102 (2021) - 2020
- [i1]Oskar Allerbo, Rebecka Jörnsten:
Flexible, Non-parametric Modeling Using Regularized Neural Networks. CoRR abs/2012.11369 (2020)
2010 – 2019
- 2017
- [j5]Rasmus Magnusson
, Guido Pio Mariotti, Mattias Köpsén
, William Lövfors
, Danuta R. Gawel, Rebecka Jörnsten, Jörg Linde, Torbjörn E. M. Nordling
, Elin Nyman
, Sylvie Schulze, Colm E. Nestor, Huan Zhang, Gunnar Cedersund, Mikael Benson, Andreas Tjärnberg
, Mika Gustafsson:
LASSIM - A network inference toolbox for genome-wide mechanistic modeling. PLoS Comput. Biol. 13(6) (2017)
2000 – 2009
- 2007
- [j4]Rebecka Jörnsten, Ming Ouyang, Hui-Yu Wang:
A meta-data based method for DNA microarray imputation. BMC Bioinform. 8 (2007) - 2005
- [j3]Rebecka Jörnsten, Hui-Yu Wang, William J. Welsh, Ming Ouyang:
DNA microarray data imputation and significance analysis of differential expression. Bioinform. 21(22): 4155-4161 (2005) - 2003
- [j2]Rebecka Jörnsten, Bin Yu:
Simultaneous Gene Clustering and Subset Selection for Sample Classification Via MDL. Bioinform. 19(9): 1100-1109 (2003) - [j1]Rebecka Jörnsten, Wei Wang, Bin Yu, Kannan Ramchandran:
Microarray image compression: SLOCO and the effect of information loss. Signal Process. 83(4): 859-869 (2003) - 2002
- [c2]Rebecka Jörnsten, Bin Yu, Wei Wang, Kannan Ramchandran:
Compression of cDNA and inkjet microarray images. ICIP (3) 2002: 961-964 - [c1]Rebecka Jörnsten, Bin Yu:
Compression of cDNA microarray images. ISBI 2002: 38-41
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