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pro vyhledávání: '"Gonzalez Javier"'
Autor:
Pradier, Melanie F., González, Javier
Matching is a popular approach in causal inference to estimate treatment effects by pairing treated and control units that are most similar in terms of their covariate information. However, classic matching methods completely ignore the geometry of t
Externí odkaz:
http://arxiv.org/abs/2409.05459
Autor:
González, Javier, Nori, Aditya V.
Recent advances in AI have been significantly driven by the capabilities of large language models (LLMs) to solve complex problems in ways that resemble human thinking. However, there is an ongoing debate about the extent to which LLMs are capable of
Externí odkaz:
http://arxiv.org/abs/2408.08210
Autor:
Gonzalez, Javier E., Ferreira, Marcelo, Colaço, Leorando R., Holanda, Rodrigo F. L., Nunes, Rafael C.
Publikováno v:
Physics Letters B 857 (2024) 138982
In this work, we obtain Hubble constant ($H_0$) estimates by using two galaxy cluster gas mass fraction measurement samples, Type Ia supernovae luminosity distances, and the validity of the cosmic distance duality relation. Notably, the angular diame
Externí odkaz:
http://arxiv.org/abs/2405.13665
It is well-known that Einstein's equations constrain only the total energy-momentum tensor of the cosmic substratum, without specifying the characteristics of its individual constituents. Consequently, cosmological models featuring distinct decomposi
Externí odkaz:
http://arxiv.org/abs/2403.12220
Synthetic control (SC) methods have gained rapid popularity in economics recently, where they have been applied in the context of inferring the effects of treatments on standard continuous outcomes assuming linear input-output relations. In medical a
Externí odkaz:
http://arxiv.org/abs/2312.00501
Autor:
González, Javier, Nori, Aditya V.
Large language models (LLMs) are powerful AI tools that can generate and comprehend natural language text and other complex information. However, the field lacks a mathematical framework to systematically describe, compare and improve LLMs. We propos
Externí odkaz:
http://arxiv.org/abs/2311.03033
Autor:
González, Javier, Wong, Cliff, Gero, Zelalem, Bagga, Jass, Ueno, Risa, Chien, Isabel, Oravkin, Eduard, Kiciman, Emre, Nori, Aditya, Weerasinghe, Roshanthi, Leidner, Rom S., Piening, Brian, Naumann, Tristan, Bifulco, Carlo, Poon, Hoifung
The rapid digitization of real-world data offers an unprecedented opportunity for optimizing healthcare delivery and accelerating biomedical discovery. In practice, however, such data is most abundantly available in unstructured forms, such as clinic
Externí odkaz:
http://arxiv.org/abs/2311.01301
Autor:
González, Javier Sánchez
We introduce a notion of proper morphism for schematic finite spaces and prove the analogue of Grothendieck's finiteness theorem for it by means of the classic result for schemes and general descent arguments. This result also generalizes the class o
Externí odkaz:
http://arxiv.org/abs/2305.11693