Zobrazeno 1 - 10
of 5 086
pro vyhledávání: '"Fabbro P"'
In this work, we reexamine the Dailey-Townes model by systematically investigating the electric field gradient (EFG) in various chlorine compounds, dihalogens, and the uranyl ion. Through the use of relativistic molecular calculations and projection
Externí odkaz:
http://arxiv.org/abs/2410.08386
Traditional speech enhancement methods often oversimplify the task of restoration by focusing on a single type of distortion. Generative models that handle multiple distortions frequently struggle with phone reconstruction and high-frequency harmonic
Externí odkaz:
http://arxiv.org/abs/2409.11145
Autor:
Mancusi, Michele, Halychanskyi, Yurii, Cheuk, Kin Wai, Lai, Chieh-Hsin, Uhlich, Stefan, Koo, Junghyun, Martínez-Ramírez, Marco A., Liao, Wei-Hsiang, Fabbro, Giorgio, Mitsufuji, Yuki
Music timbre transfer is a challenging task that involves modifying the timbral characteristics of an audio signal while preserving its melodic structure. In this paper, we propose a novel method based on dual diffusion bridges, trained using the Coc
Externí odkaz:
http://arxiv.org/abs/2409.06096
Autor:
Lee, Sungho, Martínez-Ramírez, Marco, Liao, Wei-Hsiang, Uhlich, Stefan, Fabbro, Giorgio, Lee, Kyogu, Mitsufuji, Yuki
We present GRAFX, an open-source library designed for handling audio processing graphs in PyTorch. Along with various library functionalities, we describe technical details on the efficient parallel computation of input graphs, signals, and processor
Externí odkaz:
http://arxiv.org/abs/2408.03204
Autor:
Fraser, Wesley C., Porter, Simon B., Peltier, Lowell, Kavelaars, JJ, Verbiscer, Anne J., Buie, Marc W., Stern, S. Alan, Spencer, John R., Benecchi, Susan D., Terai, Tsuyoshi, Ito, Takashi, Yoshida, Fumi, Gerdes, David W., Napier, Kevin J., Lin, Hsing Wen, Gwyn, Stephen D. J., Smotherman, Hayden, Fabbro, Sebastien, Singer, Kelsi N., Alexander, Amanda M., Arimatsu, Ko, Banks, Maria E., Bray, Veronica J., El-Maarry, Mohamed Ramy, Ferrell, Chelsea L., Fuse, Tetsuharu, Glass, Florian, Holt, Timothy R., Hong, Peng, Ishimaru, Ryo, Johnson, Perianne E., Lauer, Tod R., Leiva, Rodrigo, Lykawka, Patryk S., Marschall, Raphael, Núñez, Jorge I., Postman, Marc, Quirico, Eric, Rhoden, Alyssa R., Simpson, Anna M., Schenk, Paul, Skrutskie, Michael F., Steffl, Andrew J., Throop, Henry
We report the detection of 239 trans-Neptunian Objects discovered through the on-going New Horizons survey for distant minor bodies being performed with the Hyper Suprime-Cam mosaic imager on the Subaru Telescope. These objects were discovered in ima
Externí odkaz:
http://arxiv.org/abs/2407.21142
Recent research endeavours have theoretically shown the beneficial effect of cooperation in multi-agent reinforcement learning (MARL). In a setting involving $N$ agents, this beneficial effect usually comes in the form of an $N$-fold linear convergen
Externí odkaz:
http://arxiv.org/abs/2407.20441
Autor:
Ferreira, Leonardo, Bickley, Robert W., Ellison, Sara L., Patton, David R., Byrne-Mamahit, Shoshannah, Wilkinson, Scott, Bottrell, Connor, Fabbro, Sébastien, Gwyn, Stephen D. J., McConnachie, Alan
Merging and interactions can radically transform galaxies. However, identifying these events based solely on structure is challenging as the status of observed mergers is not easily accessible. Fortunately, cosmological simulations are now able to pr
Externí odkaz:
http://arxiv.org/abs/2407.18396
In this work, we have validated the application of Hertzian contact mechanics models and corrections in the framework of linear elasticity for the analysis of force vs indentation curves acquired using spherical indenters by means of finite elements
Externí odkaz:
http://arxiv.org/abs/2406.17157
Autor:
Lee, Sungho, Martínez-Ramírez, Marco A., Liao, Wei-Hsiang, Uhlich, Stefan, Fabbro, Giorgio, Lee, Kyogu, Mitsufuji, Yuki
Music mixing is compositional -- experts combine multiple audio processors to achieve a cohesive mix from dry source tracks. We propose a method to reverse engineer this process from the input and output audio. First, we create a mixing console that
Externí odkaz:
http://arxiv.org/abs/2406.01049
Autor:
Bialek, Spencer, Bertin, Emmanuel, Fabbro, Sébastien, Bouy, Hervé, Rivet, Jean-Pierre, Lai, Olivier, Cuillandre, Jean-Charles
We introduce a novel technique to mitigate the adverse effects of atmospheric turbulence on astronomical imaging. Utilizing a video-to-image neural network trained on simulated data, our method processes a sliding sequence of short-exposure ($\sim$0.
Externí odkaz:
http://arxiv.org/abs/2405.05250