Semi-unsupervised Bayesian convex image restoration with location mixture of Gaussian. - François Orieux; Raphael Chinchilla (EUSIPCO, 2017)

Optimization-based Estimation of Expected Values with Application to Stochastic Programming. - Raphael Chinchilla; João P. Hespanha 001 (CDC, 2019)

A Tale of Two Doses: Model Identification and Optimal Vaccination for COVID-19. - Raphael Chinchilla; Guosong Yang; Murat K. Erdal; Ramon R. Costa; João P. Hespanha 001 (CDC, 2021)

Forecasting COVID-19 cases based on a parameter-varying stochastic SIR model. - João P. Hespanha 001; Raphael Chinchilla; Ramon R. Costa; Murat K. Erdal; Guosong Yang (Annu. Rev. Control., 2021)

Newton and interior-point methods for (constrained) nonconvex-nonconcave minmax optimization with stability guarantees. - Raphael Chinchilla; Guosong Yang; João Pedro Hespanha (CoRR, 2022)

Learning Residual Dynamics via Physics-Augmented Neural Networks: Application to Vapor Compression Cycles. - Raphael Chinchilla; Vedang M. Deshpande; Ankush Chakrabarty; Christopher R. Laughman (ACC, 2023)

Convergent Second-Order Methods for Min-Max Optimizations. - Raphael Chinchilla; Guosong Yang; João P. Hespanha 001 (ACC, 2023)

Game Theory for Autonomy: From Min-Max Optimization to Equilibrium and Bounded Rationality Learning. - Kyriakos G. Vamvoudakis; Filippos Fotiadis; João P. Hespanha 001; Raphael Chinchilla; Guosong Yang; Mushuang Liu; Jeff S. Shamma; Lacra Pavel (ACC, 2023)

Stochastic Programming Using Expected Value Bounds. - Raphael Chinchilla; João P. Hespanha 001 (IEEE Trans. Autom. Control., 2023)

Newton and interior-point methods for (constrained) nonconvex-nonconcave minmax optimization with stability and instability guarantees. - Raphael Chinchilla; Guosong Yang; João Pedro Hespanha (Math. Control. Signals Syst., 2024)