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Maria Bånkestad
Maria Bånkestad
Outros nomesMaria Margareta Bånkestad
Uppsala University; RISE Research institutes of Sweden
E-mail confirmado em ri.se
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Bayesian uncertainty quantification in linear models for diffusion MRI
J Sjölund, A Eklund, E Özarslan, M Herberthson, M Bånkestad, ...
NeuroImage 175, 272-285, 2018
202018
Graph-based neural acceleration for nonnegative matrix factorization
J Sjölund, M Bånkestad
arXiv preprint arXiv:2202.00264, 2022
132022
Variational Elliptical Processes
M Bånkestad, J Sjölund, J Taghia, TB Schön
Transactions on Machine Learning Research, 2023
10*2023
Pre-training transformers for molecular property prediction using reaction prediction
J Broberg, M Bånkestad, E Ylipää
AI for Science Workshop: ICML, 2022
92022
Ising on the graph: Task-specific graph subsampling via the Ising model
M Bånkestad, JR Andersson, S Mair, J Sjölund
arXiv preprint arXiv:2402.10206, 2024
62024
hERG-toxicity prediction using traditional machine learning and advanced deep learning techniques
E Ylipää, S Chavan, M Bånkestad, J Broberg, B Glinghammar, U Norinder, ...
Current Research in Toxicology 5, 100121, 2023
62023
Modeling, Simulation and Dynamic control of a Wave Energy Converter
M Bånkestad
52013
Carbohydrate NMR chemical shift prediction by GeqShift employing E (3) equivariant graph neural networks
M Bånkestad, KM Dorst, G Widmalm, J Rönnols
RSC advances 14 (36), 26585-26595, 2024
42024
Constructing the Matrix Multilayer Perceptron and its Application to the VAE
J Taghia, M Bånkestad, F Lindsten, TB Schön
arXiv preprint arXiv:1902.01182, 2019
32019
Flexible SE (2) graph neural networks with applications to PDE surrogates
M Bånkestad, O Mogren, A Pirinen
arXiv preprint arXiv:2405.20287, 2024
22024
Carbohydrate NMR chemical shift predictions using E (3) equivariant graph neural networks
M Bånkestad, KM Dorst, G Widmalm, J Rönnols
arXiv preprint arXiv:2311.12657, 2023
22023
Structured models for scientific machine learning: From graphs to kernels
M Bånkestad
Acta Universitatis Upsaliensis, 2025
2025
Matrix Multilayer Perceptron
J Taghia, M Bånkestad, F Lindsten, T Schön
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Artigos 1–13