Tootfinder

En réalité, le nombre de victimes de l'OKC dépasse largement les quelques survivants qui ont pu témoigner. Découvrez l'ampleur de cette tragédie ici :
https://chardonsbleus.org/la-okc-en-chiffres-estimation-conservatoire/

la OKC en chiffres - estimation conservatoire
l'OKC en nombre de victimes, c'est beaucoup plus que la quarantaine de survivants-es qui ont réussi à témoigner ou participer dans les procédures ...

Just finished "Once For Yes" by Allie Millington. A phenomenal book dealing with tragedy, gentrification, grief, and community, it's preposterously poetic, but unfortunately has a twisted neoliberal politics lurking behind the scenes that makes me hesitate to recommend it. I enjoyed it greatly, especially the tightly choreographed prose, and the plot was both very well-paced and touching. It's fun for adults but also written for kids, which makes it all the more frustrating that despite touching on gentrification, it valorizes someone who is objectively a pretty scummy landlord, and fails to interrogate land ownership or rent in the slightest. It wouldn't be nearly the same story without the way things wrap up, but that doesn't make me comfortable with the larger messages it's sending, even if I think its messaging about grief is good, including for children.
#AmReading

hier gibt es nicht zufällig jemanden, der mit dem gedanken spielt, #italienisch zu lernen, und noch #kassetten abspielen kann? 🙃
#fedigive

LayerLock: Non-collapsing Representation Learning with Progressive Freezing
Goker Erdogan, Nikhil Parthasarathy, Catalin Ionescu, Drew Hudson, Alexander Lerchner, Andrew Zisserman, Mehdi Sajjadi, Joao Carreira
https://arxiv.org/abs/2509.10156

LayerLock: Non-collapsing Representation Learning with Progressive Freezing
We introduce LayerLock, a simple yet effective approach for self-supervised visual representation learning, that gradually transitions from pixel to latent prediction through progressive layer freezing. First, we make the observation that during training of video masked-autoencoding (MAE) models, ViT layers converge in the order of their depth: shallower layers converge early, deeper layers converge late. We then show that this observation can be exploited to accelerate standard MAE by progress…

ALIGNS: Unlocking nomological networks in psychological measurement through a large language model
Kai R. Larsen, Sen Yan, Roland M\"uller, Lan Sang, Mikko R\"onkk\"o, Ravi Starzl, Donald Edmondson
https://arxiv.org/abs/2509.09723

ALIGNS: Unlocking nomological networks in psychological measurement through a large language model
Psychological measurement is critical to many disciplines. Despite advances in measurement, building nomological networks, theoretical maps of how concepts and measures relate to establish validity, remains a challenge 70 years after Cronbach and Meehl proposed them as fundamental to validation. This limitation has practical consequences: clinical trials may fail to detect treatment effects, and public policy may target the wrong outcomes. We introduce Analysis of Latent Indicators to Generate …

Inverse Synthetic Aperture Radar, Radar Cross Section, and Iterative Smooth Reweighting $\ell_1$-minimization
Christer Larsson
https://arxiv.org/abs/2508.10536 https://

Inverse Synthetic Aperture Radar, Radar Cross Section, and Iterative Smooth Reweighting $\ell_1$-minimization
Radar Cross Section measurement data is often analyzed using Inverse Synthetic Aperture Radar images. This paper compares backprojection and iterative smooth reweighted $\ell_1$-minimization as methods to analyze radar cross section measurements and extract radar cross section for parts of the measured object. The main conclusion is that using backprojection images to extract RCS is robust and accurate but is more limited by the resolution than iterative smooth reweighted $\ell_1$-minimization.…

Ruggedized Ultrasound Sensing in Harsh Conditions: eRTIS in the wild
Dennis Laurijssen, Wouter Jansen, Arne Aerts, Walter Daems, Jan Steckel
https://arxiv.org/abs/2509.10029 htt…

Ruggedized Ultrasound Sensing in Harsh Conditions: eRTIS in the wild
We present eRTIS, a rugged, embedded ultrasound sensing system for use in harsh industrial environments. The system features a broadband capacitive transducer and a 32-element MEMS microphone array capable of 2D and 3D beamforming. A modular hardware architecture separates sensing and processing tasks: a high-performance microcontroller handles excitation signal generation and data acquisition, while an NVIDIA Jetson module performs GPU-accelerated signal processing. eRTIS supports external syn…

Nonlinear filtering based on density approximation and deep BSDE prediction
Kasper B{\aa}gmark, Adam Andersson, Stig Larsson
https://arxiv.org/abs/2508.10630 https://

Nonlinear filtering based on density approximation and deep BSDE prediction
A novel approximate Bayesian filter based on backward stochastic differential equations is introduced. It uses a nonlinear Feynman--Kac representation of the filtering problem and the approximation of an unnormalized filtering density using the well-known deep BSDE method and neural networks. The method is trained offline, which means that it can be applied online with new observations. A mixed a priori-a posteriori error bound is proved under an elliptic condition. The theoretical convergence …

Crosslisted article(s) found for stat.ME. https://arxiv.org/list/stat.ME/new
[1/1]:
- ALIGNS: Unlocking nomological networks in psychological measurement through a large language model
Kai R. Larsen, Sen Yan, Roland M\"uller, Lan Sang, Mikko R\"onkk\"o, Ravi Starzl, Donald …

Euclid: Early Release Observations -- The star cluster systems of the Local Group dwarf galaxies IC 10 and NGC 6822
J. M. Howell, A. M. N. Ferguson, S. S. Larsen, A. Lan\c{c}on, F. Annibali, J. -C. Cuillandre, L. K. Hunt, D. Mart\'inez-Delgado, D. Massari, T. Saifollahi, K. Voggel, B. Altieri, S. Andreon, N. Auricchio, C. Baccigalupi, M. Baldi, S. Bardelli, A. Biviano, E. Branchini, M. Brescia, J. Brinchmann, S. Camera, G. Ca\~nas-Herrera, G. P. Candini, V. Capobianco, C. Carbone, …

Euclid: Early Release Observations -- The star cluster systems of the Local Group dwarf galaxies IC 10 and NGC 6822
Star clusters are valuable indicators of galaxy evolution, offering insights into the buildup of stellar populations across cosmic time. Understanding intrinsic star cluster populations of dwarf galaxies is particularly important given their role in the hierarchical growth of larger systems. Using Euclid Early Release Observation data, we study star clusters in two star-forming dwarf irregulars in the Local Group, NGC 6822 and IC 10 [$M_\star \sim$ (1--4) $\times10^8 M_\odot$]. With Euclid, clu…