Eric Bradford - Dissemin

All papers authored by Eric Bradford

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2021 E. A. del Rio Chanona, P. Petsagkourakis

, E. Bradford

, J. E. Alves Graciano, B. Chachuat

Real-Time Optimization Meets Bayesian Optimization and Derivative-Free Optimization: A Tale of Modifier Adaptation

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2020 Eric Bradford

, Lars Imsland, Dongda Zhang, Ehecatl Antonio del Rio Chanona

Stochastic data-driven model predictive control using gaussian processes

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Leif Erik Andersson, Eric Christopher Bradford

, Lars Imsland

Distributed learning for wind farm optimization with Gaussian processes*

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P. Petsagkourakis, I. O. Sandoval, E. Bradford

, D. Zhang, E. A. del Rio-Chanona

Reinforcement learning for batch bioprocess optimization

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2019 Eric Bradford

, Lars Imsland, Ehecatl Antonio del Rio-Chanona

Nonlinear model predictive control with explicit back-offs for Gaussian process state space models

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Eric Bradford

, Lars Imsland

Output feedback stochastic nonlinear model predictive control for batch processes

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Eric Bradford

, Marcus Reble, Lars Imsland

Output feedback stochastic nonlinear model predictive control of a polymerization batch process

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Eric Bradford

, Marcus Reble, Ala Bouaswaig, Lars Imsland

Economic stochastic nonlinear model predictive control of a semi-batch polymerization reaction

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P. Petsagkourakis, I. Orson Sandoval, E. Bradford

, D. Zhang, E. A. del Rio-Chanona

Reinforcement Learning for Batch-to-Batch Bioprocess Optimisation

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Eric Bradford

, Lars Imsland

Stochastic nonlinear model predictive control of a batch fermentation process

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E. A. del Rio Chanona, J. E. Alves Graciano, E. Bradford

, B. Chachuat

Modifier-Adaptation Schemes Employing Gaussian Processes and Trust Regions for Real-Time Optimization

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This paper is made freely available by the publisher.

2018 Ehecatl Antonio Del Rio‐Chanona

, Xiaoyan Cong, Eric Bradford

, Dongda Zhang

, Keju Jing

Review of advanced physical and data‐driven models for dynamic bioprocess simulation: Case study of algae–bacteria consortium wastewater treatment

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Artur M. Schweidtmann, Adam D. Clayton, Nicholas Holmes, Eric Bradford

, Richard A. Bourne, Alexei A. Lapkin

Machine learning meets continuous flow chemistry: Automated optimization towards the Pareto front of multiple objectives

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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

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Eric Bradford

, Lars Imsland

Stochastic Nonlinear Model Predictive Control Using Gaussian Processes

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Eric Bradford

, Artur M. Schweidtmann

, Alexei Lapkin

Correction to: Efficient multiobjective optimization employing Gaussian processes, spectral sampling and a genetic algorithm

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Eric Bradford

, Artur M. Schweidtmann

, Alexei Lapkin

Efficient multiobjective optimization employing Gaussian processes, spectral sampling and a genetic algorithm

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Eric Bradford

, Lars Imsland

Stochastic NMPC of Batch Processes Using Parameterized Control Policies

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Eric Bradford

, Lars Imsland

Economic Stochastic Model Predictive Control Using the Unscented Kalman Filter

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2017 Joseph M. Reckamp

, Ashira Bindels, Sophie Duffield, Yangmu Chloe Liu, Eric Bradford

, Eric Ricci, Flavien Susanne, Andrew Rutter

Mixing Performance Evaluation for Commercially Available Micromixers Using Villermaux–Dushman Reaction Scheme with the Interaction by Exchange with the Mean Model

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All papers authored by Eric Bradford