Portfolio item number 1
Short description of portfolio item number 1
Posts by Collection
portfolio
Portfolio item number 2
Short description of portfolio item number 2
publications
Fairness seen as Global Sensitivity Analysis
Can be found in Machine Learning, 2022
This paper is about theoretical links between Group Fairness and Global Sensitivity Analysis.
Download here
talks
Talk 1 on Relevant Topic in Your Field
Published:
This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
Tutorial 1 on Relevant Topic in Your Field
Published:
Talk 2 on Relevant Topic in Your Field
Published:
Conference Proceeding talk 3 on Relevant Topic in Your Field
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
L1 - Numerical Methods
Undergraduate level, Practical sessions, Université Paul Sabatier, 2019 -- 2020
Name of the course: Numerical methods
Type: Practical sessions
Level: Undergraduate (L1, computer science)
Dates: From 2019 to 2020 (1 year)
Aborded notions: Syllabus, p27 (in French)
L3 - Statistics
Undergraduate level, Complete course, Université Paul Sabatier, 2020 -- 2022
Name of the course: Introduction to Statistics
Type: Complete course
Level: Undergraduate (L3, Biology)
Dates: From 2020 to 2022 (2 years)
Aborded notions: Syllabus, p16 (in French). Introduction to statistics: Random variables, estimation, confidence interval, tests.
M1 - Stochastic Simulations
Graduate level, Practical sessions, Université Paul Sabatier, 2019 -- 2022
Name of the course: Stochastic Simulations
Type: Practical sessions
Level: Graduate (M1)
Dates: From 2019 to 2022 (3 years)
Aborded notions: Simulations using Monte-Carlo, Gaussian models, Kalman Filter, MCMC, Branching Processes, Importance Sampling, Poisson Processes…
M2 - Machine Learning
Graduate level, Practical sessions, Université Paul Sabatier, 2019 -- 2022
Name of the course: Big Data / Machine Learning
Type: Practical sessions
Level: Graduate (M2)
Dates: From 2019 to 2022 (3 years)
Aborded notions: (Un)supervised learning, classical tools such as k-NN, Neural Networks, Random Forest, Hierarchical Clustering…