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pro vyhledávání: '"A., Bertrand"'
Autor:
Jazaeri, Farzan, Shalchian, Majid, Yesayan, Ashkhen, Rassekh, Amin, Mangla, Anurag, Parvais, Bertrand, Sallese, Jean-Michel
This paper introduces a simplified and design-oriented version of the EPFL HEMT model [1], focusing on the normalized transconductance-to-current characteristic (Gm/ID ). Relying on these figures, insights into GaN HEMT modeling in relation to techno
Externí odkaz:
http://arxiv.org/abs/2409.03589
We tune the onset of optical response in aluminium kinetic inductance detectors from a natural cutoff frequency of 90 GHz to 60 GHz by applying an external magnetic field. The change in spectral response is due to the decrease of the superconducting
Externí odkaz:
http://arxiv.org/abs/2409.03356
In this work, we consider a general time-periodic linear transport equation with integral source term. We prove the existence of a Floquet principal eigenvalue, namely a real number such that the equation rescaled by this number admits nonnegative pe
Externí odkaz:
http://arxiv.org/abs/2409.01868
Publikováno v:
PNAS, August 12, 2024, 121 (34) e2408226121
Triton and Pluto are believed to share a common origin, both forming initially in the Kuiper Belt but Triton being later captured by Neptune. Both objects display similar sizes, densities, and atmospheric and surface ice composition, with the presenc
Externí odkaz:
http://arxiv.org/abs/2409.01122
Rare events play a crucial role in understanding complex systems. Characterizing and analyzing them in scale-invariant situations is challenging due to strong correlations. In this work, we focus on characterizing the tails of probability distributio
Externí odkaz:
http://arxiv.org/abs/2409.01250
Computational modeling is an integral part of catalysis research. With it, new methodologies are being developed and implemented to improve the accuracy of simulations while reducing the computational cost. In particular, specific machine-learning te
Externí odkaz:
http://arxiv.org/abs/2408.14577
Causal machine learning (ML) promises to provide powerful tools for estimating individual treatment effects. Although causal ML methods are now well established, they still face the significant challenge of interpretability, which is crucial for medi
Externí odkaz:
http://arxiv.org/abs/2408.13002
Autor:
Renault, Aurélien, Achenchabe, Youssef, Bertrand, Édouard, Bondu, Alexis, Cornuéjols, Antoine, Lemaire, Vincent, Dachraoui, Asma
\texttt{ml\_edm} is a Python 3 library, designed for early decision making of any learning tasks involving temporal/sequential data. The package is also modular, providing researchers an easy way to implement their own triggering strategy for classif
Externí odkaz:
http://arxiv.org/abs/2408.12925
Autor:
Karageorgiou, Dimitrios, Bammey, Quentin, Porcellini, Valentin, Goupil, Bertrand, Teyssou, Denis, Papadopoulos, Symeon
Synthetic images disseminated online significantly differ from those used during the training and evaluation of the state-of-the-art detectors. In this work, we analyze the performance of synthetic image detectors as deceptive synthetic images evolve
Externí odkaz:
http://arxiv.org/abs/2408.11541
Autor:
Zhang, Zheng, Cai, Yanzhen, Jiao, Jinlong, Kang, Jing, Yu, Dehong, Roessli, Bertrand, Zhang, Anmin, Ji, Jianting, Jin, Feng, Ma, Jie, Zhang, Qingming
YbOCl is a representative member of the van der Waals layered honeycomb rare-earth chalcohalide REChX (RE = rare earth, Ch = O, S, Se, and Te, and X = F, Cl, Br, and I) family reported recently. Its spin ground state remains to be explored experiment
Externí odkaz:
http://arxiv.org/abs/2408.10515