Incremental Global Parameter Estimation in Dynamical Systems

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Incremental Global Parameter Estimation in Dynamical Systems

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Two New Calibration Techniques of Lumped-Parameter Mathematical Models for the Cardiovascular System

Minimizing Quasi-self-concordant Functions by Gradient Regularization of Newton Method

Galerkin neural network-POD for acoustic and electromagnetic wave propagation in parametric domains

A coordinate transformation-based physics-informed neural networks for hyperbolic conservation laws

A theoretical analysis of mass scaling techniques

Nonlinear model reduction with Neural Galerkin schemes on quadratic manifolds

Learning Power Flow Models and Constraints from Time-Synchronized Measurements: A Review

Stability: a search for structure

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

SPACE-TIME REDUCED BASIS METHODS FOR PARAMETRIZED UNSTEADY STOKES EQUATIONS

Iterative Learning Optimisation and Control of MAST-U Breakdown and Early Ramp-up Scenarios

Dynamical system approach to navigation around obstacles

Data-driven Methods for Control: from Linear to Lifting

On the use of Cramér-Rao Lower Bound for least-variance circuit parameters identification of Li-ion cells

Computationally Efficient Reinforcement Learning: Targeted Exploration leveraging Simple Rules

Violation-aware contextual Bayesian optimization for controller performance optimization with unmodeled constraints

Universal and adaptive methods for robust stochastic optimization

OASIS: Optimisation-based Activity Scheduling with Integrated Simultaneous choice dimensions

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Stochastic adaptive resampling for the estimation of discrete choice models