Zobrazeno 1 - 10
of 386
pro vyhledávání: '"Rodriguez, Alexander"'
Multi-variate time series forecasting is an important problem with a wide range of applications. Recent works model the relations between time-series as graphs and have shown that propagating information over the relation graph can improve time serie
Externí odkaz:
http://arxiv.org/abs/2407.02641
We measure the radius-velocity phase-space edge profile for Abell S1063 using galaxy redshifts from arXiv:1409.3507 and arXiv:2109.03305. Combined with a cosmological model and after accounting for interlopers and sampling effects, we infer the escap
Externí odkaz:
http://arxiv.org/abs/2406.01330
Autor:
Kamarthi, Harshavardhan, Kong, Lingkai, Rodríguez, Alexander, Zhang, Chao, Prakash, B. Aditya
Probabilistic hierarchical time-series forecasting is an important variant of time-series forecasting, where the goal is to model and forecast multivariate time-series that have underlying hierarchical relations. Most methods focus on point predictio
Externí odkaz:
http://arxiv.org/abs/2310.11569
Time-series forecasting is a critical challenge in various domains and has witnessed substantial progress in recent years. Many real-life scenarios, such as public health, economics, and social applications, involve feedback loops where predictions c
Externí odkaz:
http://arxiv.org/abs/2310.06077
Autor:
Lin, Shu-Rui, Luo, Wentao, Cai, Yi-Fu, Guo, Qi, Wei, Leyao, Wang, Bo, Li, Qinxun, Su, Can-Po, Rodriguez, Alexander
We report the detection of a 282 $^{+34}_{-31}$ pc-sized core in the center of Milky Way dark matter halo at $68\%$ confidence level by using the micro-lensing event rate sky map data from the Optical Gravitational Lensing Experiment (OGLE) survey. W
Externí odkaz:
http://arxiv.org/abs/2211.00666
Autor:
Chopra, Ayush, Rodríguez, Alexander, Subramanian, Jayakumar, Quera-Bofarull, Arnau, Krishnamurthy, Balaji, Prakash, B. Aditya, Raskar, Ramesh
Mechanistic simulators are an indispensable tool for epidemiology to explore the behavior of complex, dynamic infections under varying conditions and navigate uncertain environments. Agent-based models (ABMs) are an increasingly popular simulation pa
Externí odkaz:
http://arxiv.org/abs/2207.09714
Autor:
Rodríguez, Alexander, Kamarthi, Harshavardhan, Agarwal, Pulak, Ho, Javen, Patel, Mira, Sapre, Suchet, Prakash, B. Aditya
The COVID-19 pandemic has brought forth the importance of epidemic forecasting for decision makers in multiple domains, ranging from public health to the economy as a whole. While forecasting epidemic progression is frequently conceptualized as being
Externí odkaz:
http://arxiv.org/abs/2207.09370
Autor:
Kamarthi, Harshavardhan, Kong, Lingkai, Rodríguez, Alexander, Zhang, Chao, Prakash, B. Aditya
Probabilistic hierarchical time-series forecasting is an important variant of time-series forecasting, where the goal is to model and forecast multivariate time-series that have underlying hierarchical relations. Most methods focus on point predictio
Externí odkaz:
http://arxiv.org/abs/2206.07940
Autor:
Rodríguez, Alexander, Cui, Jiaming, Ramakrishnan, Naren, Adhikari, Bijaya, Prakash, B. Aditya
We introduce EINNs, a framework crafted for epidemic forecasting that builds upon the theoretical grounds provided by mechanistic models as well as the data-driven expressibility afforded by AI models, and their capabilities to ingest heterogeneous i
Externí odkaz:
http://arxiv.org/abs/2202.10446
Autor:
Celis-Giraldo, Carmen, Ordoñez, Diego, Díaz-Arévalo, Diana, Bohórquez, Michel D., Ibarrola, Nieves, Suárez, Carlos F., Rodríguez, Kewin, Yepes, Yoelis, Rodríguez, Alexander, Avendaño, Catalina, López-Abán, Julio, Manzano-Román, Raúl, Patarroyo, Manuel Alfonso
Publikováno v:
In Vaccine 31 May 2024 42(15):3445-3454