Signe Riemer-Sørensen

According to our database, Signe Riemer-Sørensen authored at least 20 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Fast Bayesian equipment condition monitoring via simulation based inference: applications to heat exchanger health.

Peter Collett, Alexander J. Stasik, Simone Casolo, Signe Riemer-Sørensen

CoRR, April, 2026

2025

Unreliable Uncertainty Estimates with Monte Carlo Dropout.

Aslak Djupskås, Alexander J. Stasik, Signe Riemer-Sørensen

CoRR, December, 2025

Examining the robustness of Physics-Informed Neural Networks to noise for Inverse Problems.

Aleksandra Jekic, Afroditi Natsaridou, Signe Riemer-Sørensen, Helge Langseth, Odd Erik Gundersen

CoRR, September, 2025

Road graph generator: Mapping roads at construction sites from GPS data.

Katarzyna Michalowska, Helga Margrete Bodahl Holmestad, Signe Riemer-Sørensen

Knowl. Based Syst., 2025

Recency-Weighted Temporally-Segmented Ensemble for Time Series Modeling.

Pål V. Johnsen, Eivind Bøhn, Sølve Eidnes, Filippo Remonato, Signe Riemer-Sørensen

J. Artif. Intell. Res., 2025

Multi-resolution learning with DeepONets and long short-term memory neural networks.

Katarzyna Michalowska, Somdatta Goswami, George Em Karniadakis, Signe Riemer-Sørensen

Neurocomputing, 2025

2024

Testing Topological Data Analysis for Condition Monitoring of Wind Turbines.

Simone Casolo, Alexander J. Stasik, Zhenyou Zhang, Signe Riemer-Sørensen

CoRR, 2024

Balancing the Norwegian regulated power market anno 2016 to 2022.

Pål Forr Austnes, Signe Riemer-Sørensen, David Andreas Bordvik, Christian Andre Andresen

CoRR, 2024

Neural Operator Learning for Long-Time Integration in Dynamical Systems with Recurrent Neural Networks.

Katarzyna Michalowska, Somdatta Goswami, George Em Karniadakis, Signe Riemer-Sørensen

Proceedings of the International Joint Conference on Neural Networks, 2024

2023

A Levenberg-Marquardt Algorithm for Sparse Identification of Dynamical Systems.

Mark Haring, Esten Ingar Grøtli, Signe Riemer-Sørensen, Katrine Seel, Kristian Gaustad Hanssen

IEEE Trans. Neural Networks Learn. Syst., November, 2023

Inferring feature importance with uncertainties with application to large genotype data.

Pål Vegard Johnsen, Inga Strümke, Mette Langaas, Andrew Thomas DeWan, Signe Riemer-Sørensen

PLoS Comput. Biol., March, 2023

DON-LSTM: Multi-Resolution Learning with DeepONets and Long Short-Term Memory Neural Networks.

Katarzyna Michalowska, Somdatta Goswami, George Em Karniadakis, Signe Riemer-Sørensen

CoRR, 2023

Pseudo-Hamiltonian system identification.

Sigurd Holmsen, Sølve Eidnes, Signe Riemer-Sørensen

CoRR, 2023

2022

Port-Hamiltonian Neural Networks with State Dependent Ports.

Sølve Eidnes, Alexander J. Stasik, Camilla Sterud, Eivind Bøhn, Signe Riemer-Sørensen

CoRR, 2022

Mutual information estimation for graph convolutional neural networks.

Marius Cervera Landsverk, Signe Riemer-Sørensen

Proceedings of the 2022 Northern Lights Deep Learning Workshop, 2022

2021

Inferring feature importance with uncertainties in high-dimensional data.

Pål Vegard Johnsen, Inga Strümke, Signe Riemer-Sørensen, Andrew Thomas DeWan, Mette Langaas

CoRR, 2021

A new method for exploring gene-gene and gene-environment interactions in GWAS with tree ensemble methods and SHAP values.

Pål V. Johnsen, Signe Riemer-Sørensen, Andrew Thomas DeWan, Megan E. Cahill, Mette Langaas

BMC Bioinform., 2021

2020

Deep Reinforcement Learning for Long Term Hydropower Production Scheduling.

Signe Riemer-Sørensen, Gjert Hovland Rosenlund

CoRR, 2020

Improved VIV response prediction using adaptive parameters and data clustering.

Jie Wu, Decao Yin, Halvor Lie, Signe Riemer-Sørensen, Svein Sævik, Michael S. Triantafyllou

CoRR, 2020

2019

Data-Driven Prediction of Vortex-Induced Vibration Response of Marine Risers Subjected to Three-Dimensional Current.

Signe Riemer-Sørensen, Jie Wu, Halvor Lie, Svein Sævik, Sang-Woo Kim

Proceedings of the Nordic Artificial Intelligence Research and Development, 2019