Mathematics

Cours 05 - Fonctions d'incidence

Bayes' theorem

Multi-Dimensional Gaussian Probability Density Functions

Cours 07 - Étapes de l'analyse mathématique des modèles, R0 et la taille finale d'une épidémie

Cours 07 - Étapes de l'analyse mathématique des modèles, R0 et la taille finale d'une épidémie

Cours 06 - Le modèle de Kermack et McKendrick

Cours 06 - Le modèle de Kermack et McKendrick

Cours 14 - Modèles dans des métapopulations

Cours 14 - Modèles dans des métapopulations

Cours 04 - Le modèle SIS

Cours 04 - Le modèle SIS

Normal forms of proofs in natural deduction II: complexity

But what is a convolution?

Normal forms of proofs in natural deduction I: existence and uniqueness

Researchers thought this was a bug (Borwein integrals)

Qiskit FalllFest CIC-IPN Mexico 2022- Combinatorial optimisation through OpenQAOA

Introduction to Quadratic Programming

History of Mathematical Logic in China: From its beginnings to Tsinghua University

Organisation of the course and brief introduction to Mathematical Epidemiology

Introduction to Mathematical Epidemiology: the SIS and Kermack and McKendrick epidemiological models

What makes a great math explanation? | SoME2 results

How to lie using visual proofs

Learning About Quantum States 6: Central Limit Theorems and more for the RSK process on random words

Learning About Quantum States 5: The Robinson--Schensted--Knuth Algorithm

Olympiad level counting (Generating functions)

Mathematical Epidemiology - Practicum 03 - Analysis and study of stochastic models in R

Mathematical Epidemiology - Practicum 02 - Model analysis, studying large-scale models in R

Mathematical Epidemiology - Lecture 09 - Some oddities and some recent mathematical models

Mathematical Epidemiology - Lecture 07 - Stochastic models

Mathematical Epidemiology - Practicum 01 - Introduction to R, getting data, solving ODE and fitting

Mathematical Epidemiology - Lecture 06 - Stochastic aspects in the spread of epidemics

Mathematical Epidemiology - Lecture 04 - Group models

UofM - MATH2740 - Lecture 09 - Part 1 - SVD (an example by hand)

UofM - MATH2740 - Lecture 07 - Part 1 - Computing and using the QR factorisation

UofM - MATH2740 - Lecture 06 - Part 2 - QR factorisation (example)

UofM - MATH 2740 - Lecture 23 - Part 2 - Markov chains in R

UofM - MATH 2740 - Lecture 23 - Part 1- Absorbing Markov chains

UofM - MATH 2740 - Lecture 22 - Regular Markov chains

UofM - MATH 2740 - Lecture 21 - Part 2 - Markov chains

UofM - MATH 2740 - Lecture 21 - Part 1 - Graph theory (Air transport in MB)

UofM - MATH 2740 - Lecture 20 - Graph theory (Air transport in MB)

UofM - MATH 2740 - Lecture 18 - Graph theory (Graph measures 2)

UofM - MATH 2740 - Lecture 17 - Part 2 - Graph theory (Graph measures 1)

UofM - MATH 2740 - Lecture 17 - Part 1 - Graph theory (Introduction to RMarkdown)