Eric Bradford

Orcid: 0000-0002-0803-0576

According to our database1, Eric Bradford authored at least 15 papers between 2018 and 2021.

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

Timeline

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Online presence:

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Bibliography

2021
Hybrid Gaussian Process Modeling Applied to Economic Stochastic Model Predictive Control of Batch Processes.
CoRR, 2021

Real-time optimization meets Bayesian optimization and derivative-free optimization: A tale of modifier adaptation.
Comput. Chem. Eng., 2021

2020
Modifier Adaptation Meets Bayesian Optimization and Derivative-Free Optimization.
CoRR, 2020

Chance Constrained Policy Optimization for Process Control and Optimization.
CoRR, 2020

Constrained Reinforcement Learning for Dynamic Optimization under Uncertainty.
CoRR, 2020

Reinforcement learning for batch bioprocess optimization.
Comput. Chem. Eng., 2020

Stochastic data-driven model predictive control using gaussian processes.
Comput. Chem. Eng., 2020

Distributed learning for wind farm optimization with Gaussian processes.
Proceedings of the 2020 American Control Conference, 2020

2019
Output feedback stochastic nonlinear model predictive control for batch processes.
Comput. Chem. Eng., 2019

Output feedback stochastic nonlinear model predictive control of a polymerization batch process.
Proceedings of the 17th European Control Conference, 2019

Nonlinear model predictive control with explicit back-offs for Gaussian process state space models.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019

2018
Correction to: Efficient multiobjective optimization employing Gaussian processes, spectral sampling and a genetic algorithm.
J. Glob. Optim., 2018

Efficient multiobjective optimization employing Gaussian processes, spectral sampling and a genetic algorithm.
J. Glob. Optim., 2018

Dynamic modeling and optimization of sustainable algal production with uncertainty using multivariate Gaussian processes.
Comput. Chem. Eng., 2018

Stochastic Nonlinear Model Predictive Control Using Gaussian Processes.
Proceedings of the 16th European Control Conference, 2018


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