110 http://isa.epfl.ch/imoniteur_ISAP/ itffichecours.txt?path=EPFL.Etu.FicheCours.HeaderEN itffichecours.txt?path=EPFL.Etu.FicheCours.GlobalNav_js en 2026 2141273 2141273 2301874322 2301874322 1 0 Physics (edoc) EDPY !itffichecours.htm?ww_i_matiere=2954525563&ww_x_anneeAcad=2301874322&ww_i_section=2141273&ww_i_niveau= 1946250234 1946250250 2021-2022 COURSE BOOKLET PHYS-754 Lecture series on scientific machine learning Lecture series on scientific machine learning Lecturers Carleo Giuseppe, Ceriotti Michele, Corminboeuf Clémence, De Los Rios Paolo, Mathis Alexander, Wyart Matthieu, Zdeborová Lenka Language of teaching English Cursus Electrical Engineering (edoc)(2021-2022, EDEE 2021-22)
Materials Science and Engineering (edoc)(2021-2022, EDMX 2021-22)
Neuroscience (edoc)(2021-2022, EDNE 2021-22)
Physics (edoc)(2021-2022, EDPY 2021-22)
SemesterMand.OptionFilières
x
 Credits 2 Session Workload 60h Exam Oral presentation Number of positions Hours 42
Courses 14
Project 28
Study planSemesterMand.OptionFilières
EDEE - Electrical Engineering 2021-22x
EDMX - Materials science and Engineering 2021-22x
EDNE - Neuroscience 2021-22x
EDPY - Physics 2021-22x
Cursus Sem. Type
Electrical Engineering Opt.
Materials Science and Engineering Opt.
Neuroscience Opt.
Physics Opt.
Frequency Every year Summary This lecture presents ongoing work on how scientific questions can be tackled using machine learning. Machine learning enables extracting knowledge from data computationally and in an automatized way. We will learn on examples how this is influencing the very scientific method. Content

Machine learning is a data analysis and computational tool that in the last two decades brought groundbreaking progress into many modern technologies. What is more, machine learning is becoming an indispensable tool enabling progress in many scientific disciplines where knowledge is deduced from data.

This course will present some recent works in this direction. In the first part of the course works of different EPFL laboratories that use machine learning to address scientific questions in physics, chemistry, material science and biology will be presented.

Professors involved include: Lenka Zdeborova, Giuseppe Carleo, Michele Ceriotti, Clemence Corminboeuf, Matthieu Wyart, Alexander Mathis, Paolo De los Rios. Examples of problems covered include neural-network enhanced solutions of the Schrodinger equation in a variety of contexts, machine learning for the prediction and rationalization of chemical and physical properties of materials, analysis of proteins from their sequence and structure, or automated data analysis and modeling brain-function in neuroscience. In the second part of the lecture students will read, present and discuss selected recent articles on the subject.

Prior basic notions of machine learning are required, any of the introductory courses to machine learning is suitable. This lecture is accessible to all students across disciplines interested in natural and computational sciences.

 

 Keywords

machine learning, neural networks, scientific machine learning

 Learning Outcomes By the end of the course, the student must be able to:
  • orient themselves in scientific problems where tools of machine learning may be applied
  • be able to understand and discuss the related literature
  • identify suitable questions and tools
 Resources Bibliography

Machine Learning and the Physical Sciences, Reviews of Modern Physics, arXiv: 1903.10563

 Physique (edoc), 2021-2022 Physics (edoc), 2021-2022 Ecole polytechnique fédérale de Lausanne EPFL Ecole polytechnique fédérale de Lausanne EPFL 2021-2022 Physique (edoc) EDPY Physics (edoc) EDPY
optionnel optional
14 Cours Courses Heure(s) Hour(s) H H Mathis Alexander 318514
Ingénierie des sciences du vivant SV Life Sciences Engineering SV
Corminboeuf Anne-Clémence 178464
Chimie et génie chimique CGC Chemistry and Chemical Engineering CGC
De Los Rios Paolo 144344
Physique PH Physics PH
Ceriotti Michele 235586
Science et génie des matériaux MX Materials Science and Engineering MX
Carleo Giuseppe 330887
Physique PH Physics PH
Wyart Matthieu 263767
Physique PH Physics PH
Zdeborová Lenka 331764
Physique PH Physics PH
28 Projet Project Heure(s) Hour(s) H H Mathis Alexander 318514
Ingénierie des sciences du vivant SV Life Sciences Engineering SV
Corminboeuf Anne-Clémence 178464
Chimie et génie chimique CGC Chemistry and Chemical Engineering CGC
Ceriotti Michele 235586
Science et génie des matériaux MX Materials Science and Engineering MX
De Los Rios Paolo 144344
Physique PH Physics PH
Carleo Giuseppe 330887
Physique PH Physics PH
Zdeborová Lenka 331764
Physique PH Physics PH
Wyart Matthieu 263767
Physique PH Physics PH
2954525563 Lecture series on scientific machine learning Lecture series on scientific machine learning 2
Exposé Oral presentation Crédit Credits 2 Session libre Session free LIB LIB
Génie électrique (edoc), 2021-2022 Electrical Engineering (edoc), 2021-2022 Ecole polytechnique fédérale de Lausanne EPFL Ecole polytechnique fédérale de Lausanne EPFL 2021-2022 Génie électrique (edoc) EDEE Electrical Engineering (edoc) EDEE
optionnel optional
14 Cours Courses Heure(s) Hour(s) H H Mathis Alexander 318514
Ingénierie des sciences du vivant SV Life Sciences Engineering SV
Corminboeuf Anne-Clémence 178464
Chimie et génie chimique CGC Chemistry and Chemical Engineering CGC
De Los Rios Paolo 144344
Physique PH Physics PH
Ceriotti Michele 235586
Science et génie des matériaux MX Materials Science and Engineering MX
Carleo Giuseppe 330887
Physique PH Physics PH
Wyart Matthieu 263767
Physique PH Physics PH
Zdeborová Lenka 331764
Physique PH Physics PH
28 Projet Project Heure(s) Hour(s) H H Mathis Alexander 318514
Ingénierie des sciences du vivant SV Life Sciences Engineering SV
Corminboeuf Anne-Clémence 178464
Chimie et génie chimique CGC Chemistry and Chemical Engineering CGC
Ceriotti Michele 235586
Science et génie des matériaux MX Materials Science and Engineering MX
De Los Rios Paolo 144344
Physique PH Physics PH
Carleo Giuseppe 330887
Physique PH Physics PH
Wyart Matthieu 263767
Physique PH Physics PH
Zdeborová Lenka 331764
Physique PH Physics PH
2954525563 Lecture series on scientific machine learning Lecture series on scientific machine learning 2
Exposé Oral presentation Crédit Credits 2 Session libre Session free LIB LIB
Science et génie des matériaux (edoc), 2021-2022 Materials Science and Engineering (edoc), 2021-2022 Ecole polytechnique fédérale de Lausanne EPFL Ecole polytechnique fédérale de Lausanne EPFL 2021-2022 Science et génie des matériaux (edoc) EDMX Materials Science and Engineering (edoc) EDMX
optionnel optional
14 Cours Courses Heure(s) Hour(s) H H Mathis Alexander 318514
Ingénierie des sciences du vivant SV Life Sciences Engineering SV
Corminboeuf Anne-Clémence 178464
Chimie et génie chimique CGC Chemistry and Chemical Engineering CGC
De Los Rios Paolo 144344
Physique PH Physics PH
Ceriotti Michele 235586
Science et génie des matériaux MX Materials Science and Engineering MX
Carleo Giuseppe 330887
Physique PH Physics PH
Wyart Matthieu 263767
Physique PH Physics PH
Zdeborová Lenka 331764
Physique PH Physics PH
28 Projet Project Heure(s) Hour(s) H H Mathis Alexander 318514
Ingénierie des sciences du vivant SV Life Sciences Engineering SV
Corminboeuf Anne-Clémence 178464
Chimie et génie chimique CGC Chemistry and Chemical Engineering CGC
Ceriotti Michele 235586
Science et génie des matériaux MX Materials Science and Engineering MX
De Los Rios Paolo 144344
Physique PH Physics PH
Carleo Giuseppe 330887
Physique PH Physics PH
Wyart Matthieu 263767
Physique PH Physics PH
Zdeborová Lenka 331764
Physique PH Physics PH
2954525563 Lecture series on scientific machine learning Lecture series on scientific machine learning 2
Exposé Oral presentation Crédit Credits 2 Session libre Session free LIB LIB
Neurosciences (edoc), 2021-2022 Neuroscience (edoc), 2021-2022 Ecole polytechnique fédérale de Lausanne EPFL Ecole polytechnique fédérale de Lausanne EPFL 2021-2022 Neurosciences (edoc) EDNE Neuroscience (edoc) EDNE
optionnel optional
14 Cours Courses Heure(s) Hour(s) H H Mathis Alexander 318514
Ingénierie des sciences du vivant SV Life Sciences Engineering SV
Corminboeuf Anne-Clémence 178464
Chimie et génie chimique CGC Chemistry and Chemical Engineering CGC
De Los Rios Paolo 144344
Physique PH Physics PH
Ceriotti Michele 235586
Science et génie des matériaux MX Materials Science and Engineering MX
Carleo Giuseppe 330887
Physique PH Physics PH
Zdeborová Lenka 331764
Physique PH Physics PH
Wyart Matthieu 263767
Physique PH Physics PH
28 Projet Project Heure(s) Hour(s) H H Mathis Alexander 318514
Ingénierie des sciences du vivant SV Life Sciences Engineering SV
Corminboeuf Anne-Clémence 178464
Chimie et génie chimique CGC Chemistry and Chemical Engineering CGC
Ceriotti Michele 235586
Science et génie des matériaux MX Materials Science and Engineering MX
De Los Rios Paolo 144344
Physique PH Physics PH
Carleo Giuseppe 330887
Physique PH Physics PH
Zdeborová Lenka 331764
Physique PH Physics PH
Wyart Matthieu 263767
Physique PH Physics PH
2954525563 Lecture series on scientific machine learning Lecture series on scientific machine learning 2
Exposé Oral presentation Crédit Credits 2 Session libre Session free LIB LIB
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