Bjarne A. Grimstad

According to our database, Bjarne A. Grimstad authored at least 22 papers between 2016 and 2025.

Collaborative distances:

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

2025

On a Closed-Loop Identification Challenge in Feedback Optimization.

Kristian Løvland, Lars Struen Imsland, Bjarne A. Grimstad

Proceedings of the IEEE Conference on Control Technology and Applications, 2025

2024

Multi-task neural networks by learned contextual inputs.

Anders T. Sandnes, Bjarne A. Grimstad, Odd Kolbjørnsen

Neural Networks, 2024

A deep latent variable model for semi-supervised multi-unit soft sensing in industrial processes.

Bjarne A. Grimstad, Kristian Løvland, Lars Struen Imsland, Vidar Gunnerud

CoRR, 2024

An updated look on the convergence and consistency of data-driven dynamical models.

Kristian Løvland, Bjarne A. Grimstad, Lars Struen Imsland

Proceedings of the 63rd IEEE Conference on Decision and Control, 2024

2023

Multi-unit soft sensing permits few-shot learning.

Bjarne A. Grimstad, Kristian Løvland, Lars Struen Imsland

CoRR, 2023

Sequential Monte Carlo applied to virtual flow meter calibration.

Anders T. Sandnes, Bjarne A. Grimstad, Odd Kolbjørnsen

CoRR, 2023

2022

Passive learning to address nonstationarity in virtual flow metering applications.

Mathilde Hotvedt, Bjarne A. Grimstad, Lars Struen Imsland

Expert Syst. Appl., 2022

Adjustment formulas for learning causal steady-state models from closed-loop operational data.

Kristian Løvland, Bjarne A. Grimstad, Lars Struen Imsland

CoRR, 2022

2021

Multi-task learning for virtual flow metering.

Anders T. Sandnes, Bjarne A. Grimstad, Odd Kolbjørnsen

Knowl. Based Syst., 2021

When is gray-box modeling advantageous for virtual flow metering?

Mathilde Hotvedt, Bjarne A. Grimstad, Dag Ljungquist, Lars Imsland

CoRR, 2021

On gray-box modeling for virtual flow metering.

Mathilde Hotvedt, Bjarne A. Grimstad, Dag Ljungquist, Lars Imsland

CoRR, 2021

Bayesian neural networks for virtual flow metering: An empirical study.

Bjarne A. Grimstad, Mathilde Hotvedt, Anders T. Sandnes, Odd Kolbjørnsen, Lars Struen Imsland

Appl. Soft Comput., 2021

2020

Mathematical programming formulations for piecewise polynomial functions.

Bjarne A. Grimstad, Brage Rugstad Knudsen

J. Glob. Optim., 2020

Identifiability and interpretability of hybrid, gray-box models.

Mathilde Hotvedt, Bjarne A. Grimstad, Lars Imsland

CoRR, 2020

Developing a Hybrid Data-Driven, Mechanistic Virtual Flow Meter - a Case Study.

Mathilde Hotvedt, Bjarne A. Grimstad, Lars Imsland

CoRR, 2020

2019

ReLU Networks as Surrogate Models in Mixed-Integer Linear Programs.

Bjarne A. Grimstad, Henrik Andersson

CoRR, 2019

ReLU networks as surrogate models in mixed-integer linear programs.

Bjarne A. Grimstad, Henrik Andersson

Comput. Chem. Eng., 2019

2018

A MIQCP formulation for B-spline constraints.

Bjarne A. Grimstad

Optim. Lett., 2018

Petroleum production optimization - A static or dynamic problem?

Bjarne A. Foss, Brage Rugstad Knudsen, Bjarne A. Grimstad

Comput. Chem. Eng., 2018

2016

Global optimization with spline constraints: a new branch-and-bound method based on B-splines.

Bjarne A. Grimstad, Anders T. Sandnes

J. Glob. Optim., 2016

Towards an objective feasibility pump for convex MINLPs.

Shaurya Sharma, Brage Rugstad Knudsen, Bjarne A. Grimstad

Comput. Optim. Appl., 2016

Global optimization of multiphase flow networks using spline surrogate models.

Bjarne A. Grimstad, Bjarne A. Foss, Richard Heddle, Malcolm Woodman

Comput. Chem. Eng., 2016