Zobrazeno 1 - 10
of 391 536
pro vyhledávání: '"Le, P."'
Autor:
Tricot, S., Ikeda, H., Tchouekem, H. -C., Breton, J. -C. Le, Yasuda, S., Krüger, P., Fèvre, P. Le, Sébilleau, D., Jaouen, T., Schieffer, P.
Photoelectron diffraction (PED) is a powerful spectroscopic technique that combines elemental resolution with a high sensitivity to the local atomic arrangement at crystal surfaces, thus providing unique fingerprints of selected atomic sites in matte
Externí odkaz:
http://arxiv.org/abs/2411.05581
Autor:
Souverin, T., Neveu, J., Betoule, M., Bongard, S., Blanc, P. E., Tanugi, J. Cohen, Dagoret-Campagne, S., Feinstein, F., Ferrari, M., Hazenberg, F., Juramy, C., Guillou, L. Le, Van Suu, A. Le, Moniez, M., Nuss, E., Plez, B., Regnault, N., Sepulveda, E., Sommer, K.
The number of type Ia supernova (SNe Ia) observations will grow significantly within the next decade, mainly thanks to the Legacy Survey of Space and Time (LSST) undertaken by the Vera Rubin Observatory in Chile. With this improvement, statistical un
Externí odkaz:
http://arxiv.org/abs/2411.03256
Many existing models struggle to predict nonlinear behavior during extreme weather conditions. This study proposes a multi-scale temporal analysis for failure prediction in energy systems using PMU data. The model integrates multi-scale analysis with
Externí odkaz:
http://arxiv.org/abs/2411.02857
Autor:
Souverin, Thierry, Neveu, Jérémy, Betoule, Marc, Bongard, Sébastien, Stubbs, Christopher W., Urbach, Elana, Brownsberger, Sasha, Blanc, Pierre Éric, Tanugi, Johann Cohen, Dagoret-Campagne, Sylvie, Feinstein, Fabrice, Hardin, Delphine, Juramy, Claire, Guillou, Laurent Le, Van Suu, Auguste Le, Moniez, Marc, Plez, Bertrand, Regnault, Nicolas, Sepulveda, Eduardo, Sommer, Kélian, Collaboration, the LSST Dark Energy Science
The measurement of type Ia supernovae magnitudes provides cosmological distances, which can be used to constrain dark energy parameters. Large photometric surveys require a substantial improvement in the calibration precision of their photometry to r
Externí odkaz:
http://arxiv.org/abs/2410.24173
Autor:
Le, Cuong Chi, Truong-Vinh, Hoang-Chau, Phan, Huy Nhat, Le, Dung Duy, Nguyen, Tien N., Bui, Nghi D. Q.
Predicting program behavior and reasoning about code execution remain significant challenges in software engineering, particularly for large language models (LLMs) designed for code analysis. While these models excel at understanding static syntax, t
Externí odkaz:
http://arxiv.org/abs/2410.23402
In this paper, we first show that increases in beam size of even just small-sized LLM (1B-7B parameters) require an extensive GPU resource consumption, leading to up to 80% of recurring crashes due to memory overloads in LLM-based APR. Seemingly simp
Externí odkaz:
http://arxiv.org/abs/2410.16655
Detecting the presence of anomalies in regression models is a crucial task in machine learning, as anomalies can significantly impact the accuracy and reliability of predictions. Random Sample Consensus (RANSAC) is one of the most popular robust regr
Externí odkaz:
http://arxiv.org/abs/2410.15133
Post-training has emerged as a crucial paradigm for adapting large-scale pre-trained models to various tasks, whose effects are fully reflected by delta parameters (i.e., the disparity between post-trained and pre-trained parameters). While numerous
Externí odkaz:
http://arxiv.org/abs/2410.13841
Currently, it is challenging to investigate aneurismal hemodynamics based on current in-vivo data such as Magnetic Resonance Imaging or Computed Tomography due to the limitations in both spatial and temporal resolutions. In this work, we investigate
Externí odkaz:
http://arxiv.org/abs/2410.12027
Quantum emulators play an important role in the development and testing of quantum algorithms, especially given the limitations of the current FTQC era. Developing high-speed, memory-optimized quantum emulators is a growing research trend, with gate
Externí odkaz:
http://arxiv.org/abs/2410.11146