Tootfinder

A train carrying Boris Johnson and the former CIA chief David Petraeus
may have been the target of a Russian drone strike
that hit a train engine near the Poland-Ukraine border, according to Ukrainian Railways.
Ukraine’s foreign ministerAndrii Sybiha described the attack as
“Putin’s terror knocking directly on the doors of the EU and Nato”.
Overnight attacks across Ukraine involving more than 450 Russian drones and missiles killed at least six people and injured…

Train carrying Boris Johnson and ex-CIA chief may have been targeted in Russian strike, officials say
Ukrainian Railways says former British PM and David Petraeus crossed into Poland shortly before drone attack near border

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Finished reading "Buckeye" by Patrick Ryan.
Two families in a small Ohio town, tangled together by one impulsive afternoon in 1945, followed across three decades of war, secrets, and quiet self-preservation.
Every character is hiding something, mostly to protect themselves, sometimes carrying the added weight of shielding others too. The result is a slow, patient portrait of emotional distance, and what time can and can't heal.
5/5 ⭐⭐⭐⭐⭐

Buckeye
That, as he saw it now, was his life’s work: trying to …

Crosslisted article(s) found for math.ST. https://arxiv.org/list/math.ST/new
[1/1]:
- Graph Causal Optimal Transport and Wasserstein Distances
Jan Ob{\l}\'oj, Vlad Tuchilus
https://arxiv.org/abs/2608.13716 https://mastoxiv.page/@arXiv_mathPR_bot/117109746090804032
- Detection of Structural Distortions in Functional Time Series
Debanjana Datta, Rituparna Sen, Nalini Ravishanker
https://arxiv.org/abs/2608.13762 https://mastoxiv.page/@arXiv_statME_bot/117109778563001128
- A Structural Characterization of Entropy Functionals
Daniel Lazarev
https://arxiv.org/abs/2608.13917 https://mastoxiv.page/@arXiv_csIT_bot/117109760641851678
- Change Point Detection and Localization in High-Dimensional Time Series
Patrick Bastian, Daria Tieplova, Nina D\"ornemann, Tim Kutta
https://arxiv.org/abs/2608.14344 https://mastoxiv.page/@arXiv_statME_bot/117109842628849962
- A distance-based theory of lottery complexity
Giulio Principi
https://arxiv.org/abs/2608.14464 https://mastoxiv.page/@arXiv_econTH_bot/117109786200544079
- Handover of In-Context Learning State Across Session Boundaries
Masahiro Kato, Taka Kato
https://arxiv.org/abs/2608.14528 https://mastoxiv.page/@arXiv_csAI_bot/117109896699069976
toXiv_bot_toot

Friday Links 26-28
A short one this week.
The management reading list gave me some new ideas and the interview with Mr. T is great.
https://christof.damian.net/2026/09/friday-links-26-28.html

A passenger train travelling from Kyiv to Warsaw
was hit by a Russian drone
two kilometres from the Polish border
in an attack that Ukraine’s foreign minister described as
“Putin’s terror knocking directly on the doors of the EU and Nato”.
Overnight attacks across Ukraine involving more than 450 Russian drones and missiles killed at least six people and injured more than 40.
Ukraine’s air force said it had intercepted 405 drones and four missiles.
We…

Train carrying Boris Johnson and ex-CIA chief may have been targeted in Russian strike, officials say
Ukrainian Railways says former British PM and David Petraeus crossed into Poland shortly before drone attack near border

Foundations of Independent Component Analysis
Patrick Forr\'e
https://arxiv.org/abs/2608.13229 https://arxiv.org/pdf/2608.13229 https://arxiv.org/html/2608.13229
arXiv:2608.13229v1 Announce Type: new
Abstract: We present the mathematical foundations of linear independent component analysis (ICA) models based on standard literature in a self-contained note. It is aimed at readers with a background in measure-theoretic probability theory. We first develop the theory of the characteristic functions of probability measures on $\mathbb{R}^d$, including their analyticity and the way in which they determine and characterise the distributions. We then focus on several identifiability results of ICA models with successively strengthened assumptions on the sources: from merely non-constant, to non-Gaussian, to Gaussian-free independent sources. Under the strictest assumptions, we show that the independent sources are identifiable up to translation, permutation, scales and signs, and this even in the presence of additive Gaussian noise. Furthermore, we present the online equivariant gradient descent ICA algorithm for recovering the independent sources from data, in the standard complete noiseless non-Gaussian ICA setting.
toXiv_bot_toot

Friday Links 26-28
A short one this week.
The management reading list gave me some new ideas and the interview with Mr. T is great.
https://christof.damian.net/2026/09/friday-links-26-28.html