Signe Riemer-Sørensen

25 papers B 1Journal 22Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Examining the robustness of Physics-Informed Neural Networks to noise for Inverse Problems. CoRR Aleksandra Jekic, Afroditi Natsaridou, Signe Riemer-Sørensen, Helge Langseth, Odd Erik Gundersen
2025	J	`jnl`	Multi-resolution learning with DeepONets and long short-term memory neural networks. Neurocomputing Katarzyna Michalowska, Somdatta Goswami, George Em Karniadakis, Signe Riemer-Sørensen
2025	J	`jnl`	Recency-Weighted Temporally-Segmented Ensemble for Time Series Modeling. J. Artif. Intell. Res. Pål V. Johnsen, Eivind Bøhn, Sølve Eidnes, Filippo Remonato, Signe Riemer-Sørensen
2025	J	`jnl`	Road graph generator: Mapping roads at construction sites from GPS data. Knowl. Based Syst. Katarzyna Michalowska, Helga Margrete Bodahl Holmestad, Signe Riemer-Sørensen
2025	J	`jnl`	Unreliable Uncertainty Estimates with Monte Carlo Dropout. CoRR Aslak Djupskås, Alexander J. Stasik, Signe Riemer-Sørensen
2024	J	`jnl`	Balancing the Norwegian regulated power market anno 2016 to 2022. CoRR Pål Forr Austnes, Signe Riemer-Sørensen, David Andreas Bordvik, Christian Andre Andresen
2024	B	`conf`	Neural Operator Learning for Long-Time Integration in Dynamical Systems with Recurrent Neural Networks. IJCNN Katarzyna Michalowska, Somdatta Goswami, George Em Karniadakis, Signe Riemer-Sørensen
2024	J	`jnl`	Recency-Weighted Temporally-Segmented Ensemble for Time-Series Modeling. CoRR Pål V. Johnsen, Eivind Bøhn, Sølve Eidnes, Filippo Remonato, Signe Riemer-Sørensen
2024	J	`jnl`	Road Graph Generator: Mapping roads at construction sites from GPS data. CoRR Katarzyna Michalowska, Helga Margrete Bodahl Holmestad, Signe Riemer-Sørensen
2024	J	`jnl`	Testing Topological Data Analysis for Condition Monitoring of Wind Turbines. CoRR Simone Casolo, Alexander Stasik, Zhenyou Zhang, Signe Riemer-Sørensen
2023	J	`jnl`	A Levenberg-Marquardt Algorithm for Sparse Identification of Dynamical Systems. IEEE Trans. Neural Networks Learn. Syst. Mark Haring, Esten Ingar Grøtli, Signe Riemer-Sørensen, Katrine Seel, Kristian Gaustad Hanssen
2023	J	`jnl`	DON-LSTM: Multi-Resolution Learning with DeepONets and Long Short-Term Memory Neural Networks. CoRR Katarzyna Michalowska, Somdatta Goswami, George Em Karniadakis, Signe Riemer-Sørensen
2023	J	`jnl`	Inferring feature importance with uncertainties with application to large genotype data. PLoS Comput. Biol. Pål Vegard Johnsen, Inga Strümke, Mette Langaas, Andrew Thomas DeWan, Signe Riemer-Sørensen
2023	J	`jnl`	Neural Operator Learning for Long-Time Integration in Dynamical Systems with Recurrent Neural Networks. CoRR Katarzyna Michalowska, Somdatta Goswami, George Em Karniadakis, Signe Riemer-Sørensen
2023	J	`jnl`	Pseudo-Hamiltonian system identification. CoRR Sigurd Holmsen, Sølve Eidnes, Signe Riemer-Sørensen
2022	J	`jnl`	A Levenberg-Marquardt algorithm for sparse identification of dynamical systems. CoRR Mark Haring, Esten Ingar Grøtli, Signe Riemer-Sørensen, Katrine Seel, Kristian Gaustad Hanssen
2022	—	`conf`	Mutual information estimation for graph convolutional neural networks. NLDL Marius Cervera Landsverk, Signe Riemer-Sørensen
2022	J	`jnl`	Mutual information estimation for graph convolutional neural networks. CoRR Marius Cervera Landsverk, Signe Riemer-Sørensen
2022	J	`jnl`	Port-Hamiltonian Neural Networks with State Dependent Ports. CoRR Sølve Eidnes, Alexander J. Stasik, Camilla Sterud, Eivind Bøhn, Signe Riemer-Sørensen
2021	J	`jnl`	A new method for exploring gene-gene and gene-environment interactions in GWAS with tree ensemble methods and SHAP values. BMC Bioinform. Pål V. Johnsen, Signe Riemer-Sørensen, Andrew Thomas DeWan, Megan E. Cahill, Mette Langaas
2021	J	`jnl`	Inferring feature importance with uncertainties in high-dimensional data. CoRR Pål Vegard Johnsen, Inga Strümke, Signe Riemer-Sørensen, Andrew Thomas DeWan, Mette Langaas
2020	J	`jnl`	Deep Reinforcement Learning for Long Term Hydropower Production Scheduling. CoRR Signe Riemer-Sørensen, Gjert Hovland Rosenlund
2020	J	`jnl`	Improved VIV response prediction using adaptive parameters and data clustering. CoRR Jie Wu, Decao Yin, Halvor Lie, Signe Riemer-Sørensen, Svein Sævik, Michael S. Triantafyllou
2019	—	`conf`	Data-Driven Prediction of Vortex-Induced Vibration Response of Marine Risers Subjected to Three-Dimensional Current. NAIS Signe Riemer-Sørensen, Jie Wu, Halvor Lie, Svein Sævik, Sang-Woo Kim
2019	J	`jnl`	Data-driven prediction of vortex-induced vibration response of marine risers subjected to three-dimensional current. CoRR Signe Riemer-Sørensen, Jie Wu, Halvor Lie, Svein Sævik, Sang-Woo Kim