Tootfinder

GÉANT witnessing a historic moment in Marseille 🇫🇷
This week, GÉANT joined AFR-IX telecom, ASREN, the European Investment Bank, French authorities & North African operators for the first landing of the Medusa Submarine Cable System on the French coast.
This milestone has been co-financed by the European Union through the Connecting Europe Facility (CEF) programme, under AFR-IX’s ATMED–DG and ATMED Nador–DG projects.
GÉANT is proud to contribute to this effort through t…

Series B, Episode 10 - Voice from the Past
VILA: And why not? [Shouts after Avon] I'm as good as you are. [Sotto voce] Better probably.
VILA: [Takes pad off Blake] Blake, you want some water? [Holds glass while Blake drinks]
https://blake.torpidity.net/m/210/179 B7B5

Approximate Bayesian Inference via Bitstring Representations
Aleksanteri Sladek, Martin Trapp, Arno Solin
https://arxiv.org/abs/2508.13598 https://arxiv.or…

Approximate Bayesian Inference via Bitstring Representations
The machine learning community has recently put effort into quantized or low-precision arithmetics to scale large models. This paper proposes performing probabilistic inference in the quantized, discrete parameter space created by these representations, effectively enabling us to learn a continuous distribution using discrete parameters. We consider both 2D densities and quantized neural networks, where we introduce a tractable learning approach using probabilistic circuits. This method offers …

Rings of Light, Speed of AI: YOLO for Cherenkov Reconstruction
Martino Borsato, Giovanni Lagan\`a, Maurizio Martinelli
https://arxiv.org/abs/2509.26273 https://

Rings of Light, Speed of AI: YOLO for Cherenkov Reconstruction
Cherenkov rings play a crucial role in identifying charged particles in high-energy physics (HEP) experiments. Most Cherenkov ring pattern reconstruction algorithms currently used in HEP experiments rely on a likelihood fit to the photo-detector response, which often consumes a significant portion of the computing budget for event reconstruction. We present a novel approach to Cherenkov ring reconstruction using YOLO, a computer vision algorithm capable of real-time object identification with a…