Tootfinder

Możecie (lub nie) kojarzyć bajzel wokół przejęcia #Freenode. Niemniej, za sprawą otwartości protokołu #IRC, wiele projektów mogło przenieść się na #LiberaChat z ograniczonymi do minimum trudnościami.
Dobra wiado…

An iterated $I$-projection procedure for solving the generalized minimum information checkerboard copula problem
Ivan Kojadinovic, Tommaso Martini
https://arxiv.org/abs/2509.02829

An iterated $I$-projection procedure for solving the generalized minimum information checkerboard copula problem
The minimum information copula principle initially suggested in \cite{MeeBed97} is a maximum entropy-like approach for finding the least informative copula, if it exists, that satisfies a certain number of expectation constraints specified either from domain knowledge or the available data. We first propose a generalization of this principle allowing the inclusion of additional constraints fixing certain higher-order margins of the copula. We next show that the associated optimization problem h…

A kojarzycie jak dzieci bawią się w "sklep", kupują wyimaginowane towary i płacą wyimaginowanymi pieniędzmi?
Kapitalizm działa tak samo, tylko robią to dorośli, a inni dorośli się im przyglądają z zapartym tchem, i wymieniają się jeszcze większymi wyimaginowanymi pieniędzmi, żeby mieć część udziału w ich wyimaginowanych zyskach.
#AntyKapitalizm

"Niezgoda na zastany stan rzeczy zmienia świat"
Piękne jest to zdanie.
Bardzo kojarzy mi się z innym hasłem słyszanym na demonstracjach: "różnorodność tworzy lepszy świat".

Soft Tissue Simulation and Force Estimation from Heterogeneous Structures using Equivariant Graph Neural Networks
Madina Kojanazarova, Sidady El Hadramy, Jack Wilkie, Georg Rauter, Philippe C. Cattin
https://arxiv.org/abs/2509.10125

Soft Tissue Simulation and Force Estimation from Heterogeneous Structures using Equivariant Graph Neural Networks
Accurately simulating soft tissue deformation is crucial for surgical training, pre-operative planning, and real-time haptic feedback systems. While physics-based models such as the finite element method (FEM) provide high-fidelity results, they are often computationally expensive and require extensive preprocessing. We propose a graph neural network (GNN) architecture that predicts both tissue surface deformation and applied force from sparse point clouds. The model incorporates internal anato…

Fast Unbiased Sampling of Networks with Given Expected Degrees and Strengths
Xuanchi Li, Xin Wang, Sadamori Kojaku
https://arxiv.org/abs/2509.13230 https://

Fast Unbiased Sampling of Networks with Given Expected Degrees and Strengths
The configuration model is a cornerstone of statistical assessment of network structure. While the Chung-Lu model is among the most widely used configuration models, it systematically oversamples edges between large-degree nodes, leading to inaccurate statistical conclusions. Although the maximum entropy principle offers unbiased configuration models, its high computational cost has hindered widespread adoption, making the Chung-Lu model an inaccurate yet persistently practical choice. Here, we…

Periodic TASEP and a Cylindrical dual-RSK
Tomas Kojar
https://arxiv.org/abs/2507.17954 https://arxiv.org/pdf/2507.17954

Periodic TASEP and a Cylindrical dual-RSK
We introduce a version of RSK that captures the dynamics of periodic TASEP. This work is building towards a cylindrical analogue of (AB Dieker, J Warren, 2008).