Bjarne A. Grimstad

Orcid: 0000-0002-3197-6968

According to our database1, Bjarne A. Grimstad authored at least 20 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Multi-task neural networks by learned contextual inputs.
Neural Networks, 2024

An updated look on the convergence and consistency of data-driven dynamical models.
CoRR, 2024

A deep latent variable model for semi-supervised multi-unit soft sensing in industrial processes.
CoRR, 2024

2023
Multi-unit soft sensing permits few-shot learning.
CoRR, 2023

Sequential Monte Carlo applied to virtual flow meter calibration.
CoRR, 2023

2022
Passive learning to address nonstationarity in virtual flow metering applications.
Expert Syst. Appl., 2022

Adjustment formulas for learning causal steady-state models from closed-loop operational data.
CoRR, 2022

2021
Multi-task learning for virtual flow metering.
Knowl. Based Syst., 2021

When is gray-box modeling advantageous for virtual flow metering?
CoRR, 2021

On gray-box modeling for virtual flow metering.
CoRR, 2021

Bayesian neural networks for virtual flow metering: An empirical study.
Appl. Soft Comput., 2021

2020
Mathematical programming formulations for piecewise polynomial functions.
J. Glob. Optim., 2020

Identifiability and interpretability of hybrid, gray-box models.
CoRR, 2020

Developing a Hybrid Data-Driven, Mechanistic Virtual Flow Meter - a Case Study.
CoRR, 2020

2019
ReLU networks as surrogate models in mixed-integer linear programs.
Comput. Chem. Eng., 2019

2018
A MIQCP formulation for B-spline constraints.
Optim. Lett., 2018

Petroleum production optimization - A static or dynamic problem?
Comput. Chem. Eng., 2018

2016
Global optimization with spline constraints: a new branch-and-bound method based on B-splines.
J. Glob. Optim., 2016

Towards an objective feasibility pump for convex MINLPs.
Comput. Optim. Appl., 2016

Global optimization of multiphase flow networks using spline surrogate models.
Comput. Chem. Eng., 2016


  Loading...