Zobrazeno 1 - 10
of 24 434
pro vyhledávání: '"A. Laroche"'
Autor:
Kosovari, Melissa, Buffeteau, Thierry, Thomas, Laurent, Bégin, Andrée-Anne Guay, Vellutini, Luc, Mcgettrick, James, Laroche, Gaétan, Durrieu, Marie-Christine
Publikováno v:
ACS Applied Materials & Interfaces, 2024, 16 (23), pp. 29770-29782
Biomaterial surface engineering and integrating cell-adhesive ligands are crucial in biological research and biotechnological applications. The interplay between cells and their microenvironment, influenced by chemical and physical cues, impacts cell
Externí odkaz:
http://arxiv.org/abs/2411.12332
Autor:
Zheng, Mingyang, Makaju, Rebika, Gazizulin, Rasul, Levchenko, Alex, Addamane, Sadhvikas J., Laroche, Dominique
One-dimensional Coulomb drag has been an essential tool to probe the physics of interacting Tomonaga-Luttinger liquids. To date, most experimental work has focused on the linear regime while the predictions for Luttinger liquids beyond the linear res
Externí odkaz:
http://arxiv.org/abs/2410.17569
Coulomb drag is a powerful tool to study interactions in coupled low-dimensional systems. Historically, Coulomb drag has been attributed to a frictional force arising from momentum transfer whose direction is dictated by the current flow. However rec
Externí odkaz:
http://arxiv.org/abs/2408.12737
Publikováno v:
Proceedings of Interspeech 2024
As speech processing systems in mobile and edge devices become more commonplace, the demand for unintrusive speech quality monitoring increases. Deep learning methods provide high-quality estimates of objective and subjective speech quality metrics.
Externí odkaz:
http://arxiv.org/abs/2407.04578
Autor:
Laroche, Alexander, Speagle, Joshua S.
Data-driven models for stellar spectra which depend on stellar labels suffer from label systematics which decrease model performance: the "stellar labels gap". To close the stellar labels gap, we present a stellar label independent model for $\textit
Externí odkaz:
http://arxiv.org/abs/2404.07316
Autor:
Miccini, Riccardo, Cerioli, Alessandro, Laroche, Clément, Piechowiak, Tobias, Sparsø, Jens, Pezzarossa, Luca
Despite the recent advances in model compression techniques for deep neural networks, deploying such models on ultra-low-power embedded devices still proves challenging. In particular, quantization schemes for Gated Recurrent Units (GRU) are difficul
Externí odkaz:
http://arxiv.org/abs/2402.12263
Autor:
Zang, Hongyu, Li, Xin, Zhang, Leiji, Liu, Yang, Sun, Baigui, Islam, Riashat, Combes, Remi Tachet des, Laroche, Romain
While bisimulation-based approaches hold promise for learning robust state representations for Reinforcement Learning (RL) tasks, their efficacy in offline RL tasks has not been up to par. In some instances, their performance has even significantly u
Externí odkaz:
http://arxiv.org/abs/2310.17139
Autor:
Makaju, R., Kassar, H., Daloglu, S. M., Huynh, A., Levchenko, A., Addamane, S. J., Laroche, D.
Publikováno v:
Phys. Rev. B 109, 085101 (2024)
Coulomb drag experiments have been an essential tool to study strongly interacting low-dimensional systems. Historically, this effect has been explained in terms of momentum transfer between electrons in the active and the passive layer. Here, we rep
Externí odkaz:
http://arxiv.org/abs/2310.13626
The Ribbit system is a compact Scheme implementation running on the Ribbit Virtual Machine (RVM) that has been ported to a dozen host languages. It supports a simple Foreign Function Interface (FFI) allowing extensions to the RVM directly from the pr
Externí odkaz:
http://arxiv.org/abs/2310.13589