A guided hike into quantum machine learning

8 juil. 2026, 12:30 → 9 juil. 2026, 18:40 Europe/Paris

Salle de formation (Maison de la Simulation)

Yann Beaujeault-Taudière (CEA, Maison de la Simulation)

Description

An introduction to quantum machine learning. 
With cool pictures! 
With memes! 
With food!

The lecture will cover a basic introduction to quantum neural networks, quantum kernels, and data encoding techniques, with hands-on sessions for each. More advanced topics such as barren plateaus, expressivity, and "application <-> hardware" pipelines will be brushed over but not covered in detail.

Requirements

A little background in either variational quantum algorithms or classical machine learning is useful but optional.

A basic knowledge of quantum computing (gates, circuits, measurements) is expected.

Software tools

We will use Python during the hands-on sessions. You are free to use the quantum SDK of your choice. Nonetheless, it is strongly recommended that you install Xanadau's PennyLane; Qiskit is also supported. Please make sure that you can run this example code, or reproduce it using the SDK of your choice.

mer. 8 juillet

12:30 Welcome and lunch

1 Content of the lecture & overview of the quantum stack

Orateur: Yann Beaujeault-Taudière (CEA, Maison de la Simulation)

2 What is (quantum) machine learning?

Orateur: Yann Beaujeault-Taudière (CEA, Maison de la Simulation)

3 Quantum neural networks [Theory]

Orateur: Yann Beaujeault-Taudière (CEA, Maison de la Simulation)

15:30 Coffee break

4 Quantum neural networks [Hands-on]

Orateur: Yann Beaujeault-Taudière (CEA, Maison de la Simulation)

jeu. 9 juillet

5 Data encoding [Theory + Hands-on]

10:10 Coffee break

6 Quantum kernels [Theory]

12:00 Lunch

7 Quantum kernels [Hands-on]

15:30 Coffee break, final wrap-up and questions