Zobrazeno 1 - 10
of 7 962
pro vyhledávání: '"A. Gottwald"'
Autor:
Crisanti, Giulio, Eden, Burkhard, Gottwald, Maximilian, Mastrolia, Pierpaolo, Scherdin, Tobias
Higher-point functions in N = 4 super Yang-Mills theory can be constructed using integrability by triangulating the surfaces on which Feynman graphs would be drawn. It remains hard to analytically compute the necessary re-gluing of the tiles by virtu
Externí odkaz:
http://arxiv.org/abs/2411.07330
Autor:
Cahill, Patrick H., Gottwald, Georg A.
The Hegselmann-Krause model is a prototypical model for opinion dynamics. It models the stochastic time evolution of an agent's or voter's opinion in response to the opinion of other like-minded agents. The Hegselmann-Krause model only considers the
Externí odkaz:
http://arxiv.org/abs/2410.13378
Autor:
Gottwald, Sebastian, Braun, Daniel A.
Shannon information and Shannon entropy are undoubtedly the most commonly used quantitative measures of information, cropping up in the literature across a broad variety of disciplines, often in contexts unrelated to coding theory. Here, we generaliz
Externí odkaz:
http://arxiv.org/abs/2409.20331
Autor:
Gottwald, Georg A., Reich, Sebastian
We consider the generative problem of sampling from an unknown distribution for which only a sufficiently large number of training samples are available. In this paper, we build on previous work combining Schr\"odinger bridges and Langevin dynamics.
Externí odkaz:
http://arxiv.org/abs/2409.07968
Autor:
Mandal, Pinak, Gottwald, Georg A.
The computationally cheap machine learning architecture of random feature maps can be viewed as a single-layer feedforward network in which the weights of the hidden layer are random but fixed and only the outer weights are learned via linear regress
Externí odkaz:
http://arxiv.org/abs/2408.03626
We consider the problem of sampling from an unknown distribution for which only a sufficiently large number of training samples are available. Such settings have recently drawn considerable interest in the context of generative modelling and Bayesian
Externí odkaz:
http://arxiv.org/abs/2401.04372
Autor:
Yue, Wenqi, Gottwald, Georg A.
We perform a stochastic model reduction of the Kuramoto-Sakaguchi model for finitely many coupled phase oscillators with phase frustration. Whereas in the thermodynamic limit coupled oscillators exhibit stationary states and a constant order paramete
Externí odkaz:
http://arxiv.org/abs/2310.20048
We consider the correlator $\langle \mathcal{L} \mathcal{K} \tilde{ \mathcal{K}} \rangle $ of the Lagrange operator of $\mathcal{N}=4$ super Yang-Mills theory and two conjugate two-excitation operators in an $su(2)$ sector. We recover the planar one-
Externí odkaz:
http://arxiv.org/abs/2310.04392
Automatically identifying bat species from their echolocation calls is a difficult but important task for monitoring bats and the ecosystem they live in. Major challenges in automatic bat call identification are high call variability, similarities be
Externí odkaz:
http://arxiv.org/abs/2309.11218
Autor:
Smith, Lauren D., Gottwald, Georg A.
Inferring the state and unknown parameters of a network of coupled oscillators, such as neurons in the brain, is of utmost importance. This task is made harder when only partial and noisy observations are available, which is a typical scenario in rea
Externí odkaz:
http://arxiv.org/abs/2309.03545