Zobrazeno 1 - 10
of 3 836
pro vyhledávání: '"Astudillo P P"'
Autor:
Cortes-Zuleta, P., Boisse, I., Ould-Elhkim, M., Wilson, T. G., Larue, P., Carmona, A., Delfosse, X., Donati, J. -F., Forveille, T., Moutou, C., Cameron, A. Collier, Artigau, E., Acuña, L., Altinier, L., Astudillo-Defru, N., Baruteau, C., Bonfils, X., Cabrit, S., Cadieux, C., Cook, N. J., Decocq, E., Diaz, R. F., Fouque, P., da Silva, J. Gomes, Grankin, K., Grouffal, S., Hara, N., Hebrard, G., Heidari, N., Martins, J. H. C., Martioli, E., Maurice, M., Scigliuto, J., Bell, J. Serrano, Sulis, S., Petit, A. C., Vivien, H. G.
We report the discovery of a super-Earth candidate orbiting the nearby mid M dwarf Gl\,725A using the radial velocity (RV) method. The planetary signal has been independently identified using high-precision RVs from the SOPHIE and SPIRou spectrograph
Externí odkaz:
http://arxiv.org/abs/2411.09506
We consider Bayesian algorithm execution (BAX), a framework for efficiently selecting evaluation points of an expensive function to infer a property of interest encoded as the output of a base algorithm. Since the base algorithm typically requires mo
Externí odkaz:
http://arxiv.org/abs/2410.20596
Autor:
Lee, Young-Suk, Gunasekara, Chulaka, Contractor, Danish, Astudillo, Ramón Fernandez, Florian, Radu
We introduce a technique for multi-document grounded multi-turn synthetic dialog generation that incorporates three main ideas. First, we control the overall dialog flow using taxonomy-driven user queries that are generated with Chain-of-Thought (CoT
Externí odkaz:
http://arxiv.org/abs/2409.11500
Autor:
Don-Yehiya, Shachar, Burtenshaw, Ben, Astudillo, Ramon Fernandez, Osborne, Cailean, Jaiswal, Mimansa, Kuo, Tzu-Sheng, Zhao, Wenting, Shenfeld, Idan, Peng, Andi, Yurochkin, Mikhail, Kasirzadeh, Atoosa, Huang, Yangsibo, Hashimoto, Tatsunori, Jernite, Yacine, Vila-Suero, Daniel, Abend, Omri, Ding, Jennifer, Hooker, Sara, Kirk, Hannah Rose, Choshen, Leshem
Human feedback on conversations with language language models (LLMs) is central to how these systems learn about the world, improve their capabilities, and are steered toward desirable and safe behaviors. However, this feedback is mostly collected by
Externí odkaz:
http://arxiv.org/abs/2408.16961
The effect of dynamical states on galaxy clusters populations. I. Classification of dynamical states
While the influence of galaxy clusters on galaxy evolution is relatively well-understood, the impact of the dynamical states of these clusters is less clear. This paper series explores how the dynamical state of galaxy clusters affects their galaxy p
Externí odkaz:
http://arxiv.org/abs/2408.02519
Autor:
Fessina, Massimiliano, Cimini, Giulio, Squartini, Tiziano, Astudillo-Estévez, Pablo, Thurner, Stefan, Garlaschelli, Diego
Production networks constitute the backbone of every economic system. They are inherently fragile as several recent crises clearly highlighted. Estimating the system-wide consequences of local disruptions (systemic risk) requires detailed information
Externí odkaz:
http://arxiv.org/abs/2408.02467
Brain-computer interfaces (BCIs) enable users to interact with the external world using brain activity. Despite their potential in neuroscience and industry, BCI performance remains inconsistent in noninvasive applications, often prioritizing algorit
Externí odkaz:
http://arxiv.org/abs/2407.11617
In recent years, Natural Language Processing (NLP) has played a significant role in various Artificial Intelligence (AI) applications such as chatbots, text generation, and language translation. The emergence of large language models (LLMs) has great
Externí odkaz:
http://arxiv.org/abs/2407.06564
Autor:
Conde-Correa, M., Aguilar, T., Capelo-Astudillo, A., Duenas-Vidal, A., Segovia, J., Ortega, P. G.
In this work we analyze the $\bar KN$ interaction in the framework of a constituent quark model. The near-threshold elastic and charge exchange cross sections are evaluated, finding a good agreement with the experimental data. Furthermore, the possib
Externí odkaz:
http://arxiv.org/abs/2407.01759
Publikováno v:
Advances in Neural Information Processing Systems, 2024
Bayesian optimization is a technique for efficiently optimizing unknown functions in a black-box manner. To handle practical settings where gathering data requires use of finite resources, it is desirable to explicitly incorporate function evaluation
Externí odkaz:
http://arxiv.org/abs/2406.20062