Zobrazeno 1 - 10
of 65 798
pro vyhledávání: '"Marchetti A."'
Autor:
Marchetti, Gionni
A data-driven approach based on unsupervised machine learning is proposed to infer the intrinsic dimensions $m^{\ast}$ of the high-dimensional trajectories of the Fermi-Pasta-Ulam-Tsingou (FPUT) model. Principal component analysis (PCA) is applied to
Externí odkaz:
http://arxiv.org/abs/2411.02058
Autor:
Bakx, T. J. L. C., Amvrosiadis, A., Bendo, G. J., Algera, H. S. B., Serjeant, S., Bonavera, L., Borsato, E., Chen, X., Cox, P., González-Nuevo, J., Hagimoto, M., Harrington, K. C., Ivison, R. J., Kamieneski, P., Marchetti, L., Riechers, D. A., Tsukui, T., van der Werf, P. P., Yang, C., Zavala, J. A., Andreani, P., Berta, S., Cooray, A. R., De Zotti, G., Eales, S., Ikeda, R., Knudsen, K. K., Mitsuhashi, I., Negrello, M., Neri, R., Omont, A., Scott, D., Tamura, Y., Temi, P., Urquhart, S. A.
We use the Atacama Large sub/Millimetre Array (ALMA) to efficiently observe spectral lines across Bands 3, 4, 5, 6, 7, and 8 at high-resolution (0.5" - 0.1") for 16 bright southern Herschel sources at $1.5 < z < 4.2$. With only six and a half hours o
Externí odkaz:
http://arxiv.org/abs/2410.16351
Recent experimental realizations of liquid-liquid phase separation of active liquid crystals have offered an insight into the interaction between phase separation, ubiquitous in soft matter and biology, and chaotic active flows. In this Letter, we us
Externí odkaz:
http://arxiv.org/abs/2410.07058
Autor:
Dey, Indrakshi, Marchetti, Nicola
The key research question we are addressing in this paper, is how local distance information can be integrated into the global structure determination, in the form of network graphs realization for IoT networks. IoT networks will be pervading every w
Externí odkaz:
http://arxiv.org/abs/2410.03204
We develop a microscopic theory for excitons and exciton polaritons in transition metal dichalcogenide (TMD) monolayers under a perpendicular static magnetic field. We obtain numerically exact solutions for the ground and excited states, accounting f
Externí odkaz:
http://arxiv.org/abs/2410.00783
We study convolutional neural networks with monomial activation functions. Specifically, we prove that their parameterization map is regular and is an isomorphism almost everywhere, up to rescaling the filters. By leveraging on tools from algebraic g
Externí odkaz:
http://arxiv.org/abs/2410.00722
A one-third monolayer of the heavy metals Sn and Pb deposited on semiconductor substrates can lead to a $\sqrt{3}\times\sqrt{3}$ surface reconstruction, constituting an exciting triangular lattice material platform. A long history of experiments iden
Externí odkaz:
http://arxiv.org/abs/2409.17350
Autor:
Simoni, Alessandro, Marchetti, Francesco, Borghi, Guido, Becattini, Federico, Davoli, Davide, Garattoni, Lorenzo, Francesca, Gianpiero, Seidenari, Lorenzo, Vezzani, Roberto
Despite the recent advances in computer vision research, estimating the 3D human pose from single RGB images remains a challenging task, as multiple 3D poses can correspond to the same 2D projection on the image. In this context, depth data could hel
Externí odkaz:
http://arxiv.org/abs/2409.11104
Relative representations are an established approach to zero-shot model stitching, consisting of a non-trainable transformation of the latent space of a deep neural network. Based on insights of topological and geometric nature, we propose two improv
Externí odkaz:
http://arxiv.org/abs/2409.10967
Autor:
García-Castellanos, Alejandro, Medbouhi, Aniss Aiman, Marchetti, Giovanni Luca, Bekkers, Erik J., Kragic, Danica
We propose HyperSteiner -- an efficient heuristic algorithm for computing Steiner minimal trees in the hyperbolic space. HyperSteiner extends the Euclidean Smith-Lee-Liebman algorithm, which is grounded in a divide-and-conquer approach involving the
Externí odkaz:
http://arxiv.org/abs/2409.05671