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pro vyhledávání: '"Laroche AS"'
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
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
Autor:
Hong, Zhang-Wei, Kumar, Aviral, Karnik, Sathwik, Bhandwaldar, Abhishek, Srivastava, Akash, Pajarinen, Joni, Laroche, Romain, Gupta, Abhishek, Agrawal, Pulkit
Publikováno v:
NeurIPS 2023
Offline policy learning is aimed at learning decision-making policies using existing datasets of trajectories without collecting additional data. The primary motivation for using reinforcement learning (RL) instead of supervised learning techniques s
Externí odkaz:
http://arxiv.org/abs/2310.04413
Publikováno v:
Research and Reports in Urology, Vol Volume 8, Pp 175-179 (2016)
Ann-Sophie Laroche,1 Robert Z Bell,1 Sarah Bezzaoucha,1 Eva Földes,2 Caroline Lamarche,1 Michel Vallée11Section of Nephrology, 2Section of Internal Medicine, Department of Medicine, Maisonneuve-Rosemont Hospital, University of Montreal, Montreal, Q
Externí odkaz:
https://doaj.org/article/c49118f4195741b4b8c073d46534cd71
Inspired by human conscious planning, we propose Skipper, a model-based reinforcement learning framework utilizing spatio-temporal abstractions to generalize better in novel situations. It automatically decomposes the given task into smaller, more ma
Externí odkaz:
http://arxiv.org/abs/2310.00229