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Cours

EE-803: Optimal networked control

Cours associés (31)

EE-736: Optimal Control for Dynamic Systems

This doctoral course provides an introduction to optimal control covering fundamental theory, numerical implementation and problem formulation for applications. ...

MATH-476: Optimal transport

The first part is devoted to Monge and Kantorovitch problems, discussing the existence and the properties of the optimal plan. The second part introduces the Wasserstein distance on measures and develops applications of optimal transport to PDEs, functiona ...

MATH-329: Continuous optimization

This course introduces students to continuous, nonlinear optimization. We study the theory of optimization with continuous variables (with full proofs), and we analyze and implement important algorithms to solve constrained and unconstrained problems. ...

CS-457: Geometric computing

This course will cover mathematical concepts and efficient numerical methods for geometric computing. We will explore the beauty of geometry and develop algorithms to simulate and optimize 2D and 3D geometric models with an emphasis towards computational d ...

PHYS-512: Statistical physics of computation

The students understand tools from the statistical physics of disordered systems, and apply them to study computational and statistical problems in graph theory, discrete optimisation, inference and machine learning. ...

FIN-414: Optimization methods

This course presents the problem of static optimization, with and without (equality and inequality) constraints, both from the theoretical (optimality conditions) and methodological (algorithms) point of view. Economics and financial applications are provi ...

EE-715: Optimal control

This doctoral course provides an introduction to optimal control covering fundamental theory, numerical implementation and problem formulation for applications. ...

AR-672: Theory or Practice ? Research by design

The seminar focuses on the particular, still little understood, type of research, done "through" design. It debates on its relevance within doctoral studies thanks to the curriculum and experience of three guest scholars. ...

CS-422: Database systems

This course is intended for students who want to understand modern large-scale data analysis systems and database systems. It covers a wide range of topics and technologies, and will prepare students to be able to build such systems as well as read and und ...

BIOENG-450: In silico neuroscience

"In silico Neuroscience" introduces students to a synthesis of modern neuroscience and state-of-the-art data management, modelling and computing technologies. ...

MGT-618: Computational research methods for social sciences

The objective of this course is to introduce doctoral students to computational methods for data-driven research in the social sciences. ...

Cours associés (31)

EE-736: Optimal Control for Dynamic Systems

This doctoral course provides an introduction to optimal control covering fundamental theory, numerical implementation and problem formulation for applications. ...

MATH-476: Optimal transport

MATH-329: Continuous optimization

CS-457: Geometric computing

PHYS-512: Statistical physics of computation

FIN-414: Optimization methods

EE-715: Optimal control

This doctoral course provides an introduction to optimal control covering fundamental theory, numerical implementation and problem formulation for applications. ...

AR-672: Theory or Practice ? Research by design

CS-422: Database systems

BIOENG-450: In silico neuroscience

"In silico Neuroscience" introduces students to a synthesis of modern neuroscience and state-of-the-art data management, modelling and computing technologies. ...

MGT-618: Computational research methods for social sciences

The objective of this course is to introduce doctoral students to computational methods for data-driven research in the social sciences. ...