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pro vyhledávání: '"Heiman, Damian"'
In pioneering work from 2019, Barcel\'o and coauthors identified logics that precisely match the expressive power of constant iteration-depth graph neural networks (GNNs) relative to properties definable in first-order logic. In this article, we give
Externí odkaz:
http://arxiv.org/abs/2405.14606
We examine the relationship of graded (multi)modal logic to counting (multichannel) message passing automata with applications to the Weisfeiler-Leman algorithm. We introduce the notion of graded multimodal types, which are formulae of graded multimo
Externí odkaz:
http://arxiv.org/abs/2401.06519
We investigate the descriptive complexity of a class of neural networks with unrestricted topologies and piecewise polynomial activation functions. We consider the general scenario where the running time is unlimited and floating-point numbers are us
Externí odkaz:
http://arxiv.org/abs/2308.06277
We consider distributed algorithms in the realistic scenario where distributed message passing is operated via circuits. We show that within this setting, modal substitution calculus MSC captures the expressive power of circuits. The translations bet
Externí odkaz:
http://arxiv.org/abs/2303.04735
Autor:
Heiman, Damian
Tässä tutkielmassa tutkitaan modaalilogiikan yhteyksiä lokaaleihin algoritmeihin. Modaalilogiikka on lauselogiikan laajennus, jossa kaavojen totuutta tutkitaan mahdollisia maailmoja mallintavissa Kripke-malleissa. Lokaalit algoritmit ovat graafeis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______4853::4d39c7d34e94bda81151551beaa28fc3
https://trepo.tuni.fi/handle/10024/121938
https://trepo.tuni.fi/handle/10024/121938