Zobrazeno 1 - 10
of 212
pro vyhledávání: '"Chen, Ryan"'
We measure the performance of in-context learning as a function of task novelty and difficulty for open and closed questions. For that purpose, we created a novel benchmark consisting of hard scientific questions, each paired with a context of variou
Externí odkaz:
http://arxiv.org/abs/2407.02028
Autor:
Chen, Ryan C.
This is the third in a sequence of four papers, where we prove the arithmetic Siegel--Weil formula in co-rank $1$ for Kudla--Rapoport special cycles on exotic smooth integral models of unitary Shimura varieties of arbitrarily large even arithmetic di
Externí odkaz:
http://arxiv.org/abs/2405.01428
Autor:
Chen, Ryan C.
This is the fourth in a sequence of four papers, where we prove the arithmetic Siegel--Weil formula in co-rank $1$ for Kudla--Rapoport special cycles on exotic smooth integral models of unitary Shimura varieties of arbitrarily large even arithmetic d
Externí odkaz:
http://arxiv.org/abs/2405.01429
Autor:
Chen, Ryan C.
This is the second in a sequence of four papers, where we prove the arithmetic Siegel--Weil formula in co-rank $1$ for Kudla--Rapoport special cycles on exotic smooth integral models of unitary Shimura varieties of arbitrarily large even arithmetic d
Externí odkaz:
http://arxiv.org/abs/2405.01427
Autor:
Chen, Ryan C.
This is the first in a sequence of four papers, where we prove the arithmetic Siegel--Weil formula in co-rank $1$ for Kudla--Rapoport special cycles on exotic smooth integral models of unitary Shimura varieties of arbitrarily large even arithmetic di
Externí odkaz:
http://arxiv.org/abs/2405.01426
Autor:
Ye, Andrew, Xu, James, Wang, Yi, Yu, Yifan, Yan, Daniel, Chen, Ryan, Dong, Bosheng, Chaudhary, Vipin, Xu, Shuai
We propose the integration of sentiment analysis and deep-reinforcement learning ensemble algorithms for stock trading, and design a strategy capable of dynamically altering its employed agent given concurrent market sentiment. In particular, we crea
Externí odkaz:
http://arxiv.org/abs/2402.01441
In recent years, social virtual reality (VR), sometimes described as the "metaverse," has become widely available. With its potential comes risks, including risks to privacy. To understand these risks, we study the identifiability of participants' mo
Externí odkaz:
http://arxiv.org/abs/2303.01430
Autor:
Chaggar, Gurpreet K., Bryant, Donald B., Chen, Ryan, Fajardo, Daniel, Jules-Culver, Zuri A., Drolia, Rishi, Oliver, Haley F.
Publikováno v:
In Food Control December 2024 166
Autor:
Chen, Ryan, Cabrera, Javier
This study aims to evaluate the performance of power in the likelihood ratio test for changepoint detection by bootstrap sampling, and proposes a hypothesis test based on bootstrapped confidence interval lengths. Assuming i.i.d normally distributed e
Externí odkaz:
http://arxiv.org/abs/2011.03718
Autor:
Ghodgaonkar, Isha, Goel, Abhinav, Bordwell, Fischer, Tung, Caleb, Aghajanzadeh, Sara, Curran, Noah, Chen, Ryan, Yu, Kaiwen, Mahapatra, Sneha, Banna, Vishnu, Kao, Gore, Lee, Kate, Hu, Xiao, Eliopolous, Nick, Chinnakotla, Akhil, Rijhwani, Damini, Kim, Ashley, Chakraborty, Aditya, Ward, Mark Daniel, Lu, Yung-Hsiang, Thiruvathukal, George K.
COVID-19 has resulted in a worldwide pandemic, leading to "lockdown" policies and social distancing. The pandemic has profoundly changed the world. Traditional methods for observing these historical events are difficult because sending reporters to a
Externí odkaz:
http://arxiv.org/abs/2005.09091