Zobrazeno 1 - 10
of 6 424
pro vyhledávání: '"Casarin, A."'
We consider two supersymmetric M5 brane probe solutions in $\textrm{AdS}_7 \times S^4$ and one in $\textrm{AdS}_4 \times S^7$ that all have the $\textrm{AdS}_3 \times S^3$ world-volume geometry. The values of the classical action of the first two M5
Externí odkaz:
http://arxiv.org/abs/2411.11626
Autor:
Casarin, Roberto, Peruzzi, Antonio
The techniques suggested in Fr\"uhwirth-Schnatter et al. (2024) concern sparsity and factor selection and have enormous potential beyond standard factor analysis applications. We show how these techniques can be applied to Latent Space (LS) models fo
Externí odkaz:
http://arxiv.org/abs/2411.02531
Autor:
Casarin, Roberto, Peruzzi, Antonio
Latent Space (LS) network models project the nodes of a network on a $d$-dimensional latent space to achieve dimensionality reduction of the network while preserving its relevant features. Inference is often carried out within a Markov Chain Monte Ca
Externí odkaz:
http://arxiv.org/abs/2408.11725
We propose a new flexible tensor model for multiple-equation regression that accounts for latent regime changes. The model allows for dynamic coefficients and multi-dimensional covariates that vary across equations. We assume the coefficients are dri
Externí odkaz:
http://arxiv.org/abs/2407.00655
Autor:
Bertolini, Tommaso, Casarin, Lorenzo
We analyse the proposal of defining the Weyl anomaly for classically non-conformal theories as $g^{mn} \langle T_{mn}\rangle - \langle g^{mn} T_{mn} \rangle$, originally put forward by M. Duff, in the case of a scalar field with quartic self-interact
Externí odkaz:
http://arxiv.org/abs/2406.12464
Neural Architecture Search (NAS) methods have shown to output networks that largely outperform human-designed networks. However, conventional NAS methods have mostly tackled the single dataset scenario, incuring in a large computational cost as the p
Externí odkaz:
http://arxiv.org/abs/2405.06994
Anomaly detection is crucial in large-scale industrial manufacturing as it helps detect and localise defective parts. Pre-training feature extractors on large-scale datasets is a popular approach for this task. Stringent data security and privacy reg
Externí odkaz:
http://arxiv.org/abs/2405.06980
The landscape of deep learning research is moving towards innovative strategies to harness the true potential of data. Traditionally, emphasis has been on scaling model architectures, resulting in large and complex neural networks, which can be diffi
Externí odkaz:
http://arxiv.org/abs/2403.15194
We compute the conformal anomalies for 6d (2,0) conformal supergravity by direct calculation in component fields. The main novel results consist of the type-B anomaly coefficients for the gravitino and the 3-form, as well as their explicit quadratic
Externí odkaz:
http://arxiv.org/abs/2403.07509
Publikováno v:
J. High Energ. Phys. 2023, 132 (2023)
Nicolai maps offer an alternative description of supersymmetric theories via nonlinear and nonlocal transformations characterized by the so-called `free-action' and `determinant-matching' conditions. The latter expresses the equality of the Jacobian
Externí odkaz:
http://arxiv.org/abs/2310.19946