Eric Bradford

Publication Activity (10 Years)

Years Active: 2018-2021
Publications (10 Years): 16

Top Topics

Reinforcement Learning

Hyperparameters

Predictive Control

Chance Constrained

Top Venues

Comput. Chem. Eng.

J. Glob. Optim.

Publications

Ehecatl Antonio del Rio-Chanona, Panagiotis Petsagkourakis, Eric Bradford, Jose Eduardo Alves Graciano, Benoît Chachuat
Real-time optimization meets Bayesian optimization and derivative-free optimization: A tale of modifier adaptation. Comput. Chem. Eng. 147 (2021)
Eric Bradford, Lars Imsland, Marcus Reble, Ehecatl Antonio del Rio-Chanona
Hybrid Gaussian Process Modeling Applied to Economic Stochastic Model Predictive Control of Batch Processes. CoRR (2021)
Panagiotis Petsagkourakis, Ilya Orson Sandoval, Eric Bradford, Dongda Zhang, Ehecatl Antonio del Rio-Chanona
Constrained Reinforcement Learning for Dynamic Optimization under Uncertainty. CoRR (2020)
Panagiotis Petsagkourakis, Ilya Orson Sandoval, Eric Bradford, Federico Galvanin, Dongda Zhang, Ehecatl Antonio del Rio-Chanona
Chance Constrained Policy Optimization for Process Control and Optimization. CoRR (2020)
Panagiotis Petsagkourakis, Ilya Orson Sandoval, Eric Bradford, Dongda Zhang, Ehecatl Antonio del Rio-Chanona
Reinforcement learning for batch bioprocess optimization. Comput. Chem. Eng. 133 (2020)
Eric Bradford, Lars Imsland, Dongda Zhang, Ehecatl Antonio del Rio-Chanona
Stochastic data-driven model predictive control using gaussian processes. Comput. Chem. Eng. 139 (2020)
Ehecatl Antonio del Rio-Chanona, Panagiotis Petsagkourakis, Eric Bradford, Jose Eduardo Alves Graciano, Benoît Chachuat
Modifier Adaptation Meets Bayesian Optimization and Derivative-Free Optimization. CoRR (2020)
Eric Bradford, Lars Imsland, Ehecatl Antonio del Rio-Chanona
Nonlinear model predictive control with explicit back-offs for Gaussian process state space models. CDC (2019)
Eric Bradford, Marcus Reble, Lars Imsland
Output feedback stochastic nonlinear model predictive control of a polymerization batch process. ECC (2019)
Eric Bradford, Lars Imsland, Dongda Zhang, Ehecatl Antonio del Rio-Chanona
Stochastic data-driven model predictive control using Gaussian processes. CoRR (2019)
Panagiotis Petsagkourakis, Ilya Orson Sandoval, Eric Bradford, Dongda Zhang, Ehecatl Antonio del Rio-Chanona
Reinforcement Learning for Batch Bioprocess Optimization. CoRR (2019)
Eric Bradford, Lars Imsland
Output feedback stochastic nonlinear model predictive control for batch processes. Comput. Chem. Eng. 126 (2019)
Eric Bradford, Lars Imsland
Stochastic Nonlinear Model Predictive Control Using Gaussian Processes. ECC (2018)
Eric Bradford, Artur M. Schweidtmann, Alexei A. Lapkin
Efficient multiobjective optimization employing Gaussian processes, spectral sampling and a genetic algorithm. J. Glob. Optim. 71 (2) (2018)
Eric Bradford, Artur M. Schweidtmann, Alexei A. Lapkin
Correction to: Efficient multiobjective optimization employing Gaussian processes, spectral sampling and a genetic algorithm. J. Glob. Optim. 71 (2) (2018)
Eric Bradford, Artur M. Schweidtmann, Dongda Zhang, Keju Jing, Ehecatl Antonio del Rio-Chanona
Dynamic modeling and optimization of sustainable algal production with uncertainty using multivariate Gaussian processes. Comput. Chem. Eng. 118 (2018)