Zobrazeno 1 - 10
of 37 480
pro vyhledávání: '"Riera Be"'
Autor:
Chen, Xin, Martinez, Jessica, Shao, Xuecheng, Riera, Marc, Paesani, Francesco, Andreussi, Oliviero, Pavanello, Michele
We present a reformulation of QM/MM as a fully quantum mechanical theory of interacting subsystems, all treated at the level of density functional theory (DFT). For the MM subsystem, which lacks orbitals, we assign an ad hoc electron density and appl
Externí odkaz:
http://arxiv.org/abs/2411.17844
We develop an excursion theory that describes the evolution of a Markov process indexed by a Levy tree away from a regular and instantaneous point $x$ of the state space. The theory builds upon a notion of local time at $x$ that was recently introduc
Externí odkaz:
http://arxiv.org/abs/2411.12717
Heisenberg's uncertainty relation does not take into account that position and momentum are defined relative to a quantum reference frame (QRF). We introduce such a QRF as a covariant phase space observable to derive novel, frame-relative uncertainty
Externí odkaz:
http://arxiv.org/abs/2411.08589
Processing Using Memory (PUM) accelerators have the potential to perform Deep Neural Network (DNN) inference by using arrays of memory cells as computation engines. Among various memory technologies, ReRAM crossbars show promising performance in comp
Externí odkaz:
http://arxiv.org/abs/2410.17931
Autor:
Winata, Genta Indra, Hudi, Frederikus, Irawan, Patrick Amadeus, Anugraha, David, Putri, Rifki Afina, Wang, Yutong, Nohejl, Adam, Prathama, Ubaidillah Ariq, Ousidhoum, Nedjma, Amriani, Afifa, Rzayev, Anar, Das, Anirban, Pramodya, Ashmari, Adila, Aulia, Wilie, Bryan, Mawalim, Candy Olivia, Cheng, Ching Lam, Abolade, Daud, Chersoni, Emmanuele, Santus, Enrico, Ikhwantri, Fariz, Kuwanto, Garry, Zhao, Hanyang, Wibowo, Haryo Akbarianto, Lovenia, Holy, Cruz, Jan Christian Blaise, Putra, Jan Wira Gotama, Myung, Junho, Susanto, Lucky, Machin, Maria Angelica Riera, Zhukova, Marina, Anugraha, Michael, Adilazuarda, Muhammad Farid, Santosa, Natasha, Limkonchotiwat, Peerat, Dabre, Raj, Audino, Rio Alexander, Cahyawijaya, Samuel, Zhang, Shi-Xiong, Salim, Stephanie Yulia, Zhou, Yi, Gui, Yinxuan, Adelani, David Ifeoluwa, Lee, En-Shiun Annie, Okada, Shogo, Purwarianti, Ayu, Aji, Alham Fikri, Watanabe, Taro, Wijaya, Derry Tanti, Oh, Alice, Ngo, Chong-Wah
Vision Language Models (VLMs) often struggle with culture-specific knowledge, particularly in languages other than English and in underrepresented cultural contexts. To evaluate their understanding of such knowledge, we introduce WorldCuisines, a mas
Externí odkaz:
http://arxiv.org/abs/2410.12705
Autor:
Nohejl, Adam, Hudi, Frederikus, Kardinata, Eunike Andriani, Ozaki, Shintaro, Machin, Maria Angelica Riera, Sun, Hongyu, Vasselli, Justin, Watanabe, Taro
Word frequency is a key variable in psycholinguistics, useful for modeling human familiarity with words even in the era of large language models (LLMs). Frequency in film subtitles has proved to be a particularly good approximation of everyday langua
Externí odkaz:
http://arxiv.org/abs/2410.03240
Hybrid quantum-classical optimization techniques, which incorporate the pre-optimization of Variational Quantum Algorithms (VQAs) using Tensor Networks (TNs), have been shown to allow for the reduction of quantum computational resources. In the parti
Externí odkaz:
http://arxiv.org/abs/2409.13924
Publikováno v:
European Wireless 2024
Cell-free massive multiple-input multiple-output (CF-mMIMO) is a breakthrough technology for beyond-5G systems, designed to significantly boost the energy and spectral efficiencies of future mobile networks while ensuring a consistent quality of serv
Externí odkaz:
http://arxiv.org/abs/2409.11871
Autor:
Gauder, Lara, Riera, Pablo, Slachevsky, Andrea, Forno, Gonzalo, Garcia, Adolfo M., Ferrer, Luciana
Automated speech analysis is a thriving approach to detect early markers of Alzheimer's disease (AD). Yet, recording conditions in most AD datasets are heterogeneous, with patients and controls often evaluated in different acoustic settings. While th
Externí odkaz:
http://arxiv.org/abs/2409.12170
Autor:
De Lorenzis, A., Casado, M. P., Estarellas, M. P., Gullo, N. Lo, Lux, T., Plastina, F., Riera, A., Settino, J.
Interest in quantum machine learning is increasingly growing due to its potential to offer more efficient solutions for problems that are difficult to tackle with classical methods. In this context, the research work presented here focuses on the use
Externí odkaz:
http://arxiv.org/abs/2409.00998