papers
Publications (8)
cs.LG2026
Embedding Linear Equality Constraints in Probabilistic Neural Networks for Dynamic Modelling
Matthew Marsh, Benoit Chachuat, Antonio del Rio Chanona
cs.LG2021
Safe Real-Time Optimization using Multi-Fidelity Gaussian Processes
Panagiotis Petsagkourakis, Benoit Chachuat, Ehecatl Antonio del Rio-Chanona
eess.SY2024
Machine learning for industrial sensing and control: A survey and practical perspective
Nathan P. Lawrence, Seshu Kumar Damarla, Jong Woo Kim +7
math.OC2020
Bayesian Approach to Probabilistic Design Space Characterization: A Nested Sampling Strategy
Kennedy P. Kusumo, Lucian Gomoescu, Radoslav Paulen +4
math.OC2016
Robust MPC via Min-Max Differential Inequalities
Mario E. Villanueva, Rien Quirynen, Moritz Diehl +2
cs.LG2022
Modern Machine Learning Tools for Monitoring and Control of Industrial Processes: A Survey
R. Bhushan Gopaluni, Aditya Tulsyan, Benoit Chachuat +6
math.OC2021
Real-Time Optimization Meets Bayesian Optimization and Derivative-Free Optimization: A Tale of Modifier Adaptation
Ehecatl Antonio del Rio-Chanona, Panagiotis Petsagkourakis, Eric Bradford +2
stat.ML2015
Bayesian Optimization with Dimension Scheduling: Application to Biological Systems
Doniyor Ulmasov, Caroline Baroukh, Benoit Chachuat +2