Tag Archives: Kyoto

Kyoto 京都 (part 2)

After some pictures from Kyoto 京都, Fall and Winter, some pictures from Spring and Summer. In two weeks, my sabbatical year at Kyoto University will come to an end. It is difficult to sum up what this year has meant. It gave me the time and space to look at things differently, to revisit projects that needed a fresh perspective, and to let new ideas emerge. But above all, it was a wonderful opportunity to discover Kyoto slowly, through everyday life and through the changing seasons. From autumn colours and winter light to cherry blossoms, summer heat and festival evenings, the city never stopped surprising me…

Optimal Transport for Actuarial Science (lecture notes)

Before leaving Kyoto to go back to Montréal (and enjoy some summer break), I uploaded some lecture notes, on Optimal Transport for Actuarial Science, on HAL (soon on ArXiv ?).

These lecture notes introduce optimal transport as a mathematical language for actuarial science. They treat losses, premiums, scores, reserves, capital scenarios, climate losses and lifetime distributions as probability measures that can be compared, transported, averaged, stressed and interpolated. The first part develops the main tools: couplings, push-forwards, discrete and continuous Kantorovich problems, duality, Wasserstein distances, quantile transport, barycenters, entropic regularization and statistical optimal transport. The second part applies these tools to risk measures, Wasserstein robustness, pricing and capital, portfolio drift, reserving cash-flow distributions, climate-prevention diagnostics, reinsurance, dependence uncertainty, capital allocation, distributional fairness diagnostics and longevity risk. Later chapters and appendices discuss counterfactual transport, dynamic formulations, unbalanced transport, Schrödinger bridges, cost engineering and computational labs in R. The emphasis is on actuarial modelling choices: the state space, the ground cost, the ambiguity radius, the reference distribution and the interpretation of the transport plan. Transport maps and couplings are used as distributional objects, not as causal claims unless additional assumptions are imposed.

(pictures will be coming in the updated version, this Fall).

Marques du passé, marques du futur

J’en parlais l’autre jour, mais à peine arrivés à Kyoto, il a fallu passer au ward office, le 区役所 (kuyakusho), pour régler les formalités de base. Parmi les guichets, les formulaires et les tampons, et à la toute fin, on nous a fait passer par un service de prévention, où l’on nous a remis un petit paquet de documents, des cartes d’aléas, des recommandations en cas de typhon, des consignes d’évacuation. En particulier, je suis reparti avec un de ces cartes où la ville se colore par profondeurs d’eau possibles.


Continue reading Marques du passé, marques du futur

Kyoto, Lecture 1

Today, I will give the very first lecture of the 数学・数理科学グローバル特別講義6について, at Kyoto University.

2025/11/04 火 09:30 – 11:30
2025/11/05 水 09:30 – 11:30
2025/11/10 月 09:30 – 11:30
2025/11/11 火 09:30 – 11:30
2025/11/13 木 09:30 – 11:30
The course will be located at 3号館127大会議室. Lecture notes are also available online.

数学・数理科学グローバル特別講義6

My upcoming lectures at Kyoto University as part of the Global Special Lecture Series in Mathematics and Mathematical Sciences (No. 6) is now on the agenda: November 4, 5, 10, 11, and 13, 2025, from 9:30 till 11:30, at the Graduate School of Science, Kyoto University.

It will be one “Fairness and Distribution in Insurance – An Actuarial Perspective”. We will explore how fairness, risk sharing, and distributional concerns intersect with actuarial science and insurance, providing both theoretical insights and practical implications.

I am truly honored to contribute to this international program and look forward to engaging with students and colleagues in Kyoto.

Global Mathematics Lecture IV, Kyoto University

this Fall I will give the “Global Mathematics Lecture IV” at Kyoto University, a series open to all graduate students across the university (not limited to mathematics). My talk will focus on “algorithmic discrimination in predictive models”, based on Insurance, Biases, Discrimination and Fairness (published last year), with a particular emphasis on applications in insurance, a topic especially relevant for students in the actuarial/insurance track of the MSc program in the Department of Mathematics. Looking forward to engaging discussions with the students!

Kyoto (京都), Japan, vs. Montréal, Canada, a first comparison

We just arrived in Kyoto (京都), Japan, from Montréal, Canada. Everything seems very different. I still have in mind the time I spent in Hong Kong (more than a year), but that was 25 years ago… Just to compare, I used wikipedia’s page of Kyoto vs. Montréal. Quite naturaly, I used the pages in French, but that was not stupid because the pages in English are more compex to read (with temperatures in °C and °F, humidity in mm and inches, etc).

urlM="https://fr.wikipedia.org/wiki/Montr%C3%A9al"
urlK="https://fr.wikipedia.org/wiki/Kyoto"
download.file(urlM,destfile = "tempMtrl.html")
download.file(urlK,destfile = "tempKt.html")
library(XML)

Then we extract the tables with important informations

tables=readHTMLTable("tempKt.html")
TK=tables[[6]]
TK[] <- lapply(TK, function(col) {
if (is.character(col)) {
col <- gsub(",", ".", col)
col <- gsub("\\s", "", col)
}
suppressWarnings(as.numeric(col))
})
tables=readHTMLTable("tempMtrl.html")
TM=tables[[7]][,-1]
TM[] <- lapply(TM, function(col) {
if (is.character(col)) {
col <- gsub("\u2212", "-", col)
col <- gsub(",", ".", col)
col <- gsub("\\s", "", col)
}
suppressWarnings(as.numeric(col))
})

and we plot them

cols <- paste0("V", 2:13)
mois <- c("JAN","FEB","MAR","APR","MAY","JUN","JUL","AUG","SEP","OCT","NOV","DEC")
yminK <- suppressWarnings(as.numeric(TK[2, cols]))
ymaxK <- suppressWarnings(as.numeric(TK[3, cols]))
yminM <- suppressWarnings(as.numeric(TM[2, cols]))
ymaxM <- suppressWarnings(as.numeric(TM[3, cols]))
y0K <- pmin(yminK, ymaxK, na.rm = TRUE)
y1K <- pmax(yminK, ymaxK, na.rm = TRUE)
y0M <- pmin(yminM, ymaxM, na.rm = TRUE)
y1M <- pmax(yminM, ymaxM, na.rm = TRUE)
x <- seq_along(cols)
plot(NA,
xlim = c(0.5, length(cols) + 0.5),
ylim = range(y0M, y1M, y0K, y1K, na.rm = TRUE),
xaxt = "n", xlab = "", ylab = "",
main = "Temperatures min-max (°C, averages)")
axis(1, at = x, labels = mois)
w <- 0.8
for (i in x) {
if (!is.na(y0[i]) && !is.na(y1[i])) {
rect(i - w/2, y0K[i], i + w/2, y1K[i],
col = "lightblue", border = "steelblue", lwd = 1.2)
}
}
for (i in x) {
if (!is.na(y0[i]) && !is.na(y1[i])) {
rect(i - w/2, y0M[i], i + w/2, y1M[i],
col = "lightcoral", border = "firebrick", lwd = 1.2)
}
}
grid(nx = NA, ny = NULL, col = "gray85")

with Kyoto in blue, Montréal in red,

of course, we can do the same for humidity

or daylight

暑いですね (atsuidesune, litt. “It’s so hot, isn’t it?”)