Zobrazeno 1 - 10
of 110
pro vyhledávání: '"Chayes, Jennifer T."'
Autor:
Rampal, Nakul, Wang, Kaiyu, Burigana, Matthew, Hou, Lingxiang, Al-Johani, Juri, Sackmann, Anna, Murayshid, Hanan S., Al-Sumari, Walaa Abdullah, Al-Abdulkarim, Arwa M., Al-Hazmi, Nahla Eid, Al-Awad, Majed O., Borgs, Christian, Chayes, Jennifer T., Yaghi, Omar M.
The rapid advancement in artificial intelligence and natural language processing has led to the development of large-scale datasets aimed at benchmarking the performance of machine learning models. Herein, we introduce 'RetChemQA,' a comprehensive be
Externí odkaz:
http://arxiv.org/abs/2405.02128
Autor:
Zheng, Zhiling, He, Zhiguo, Khattab, Omar, Rampal, Nakul, Zaharia, Matei A., Borgs, Christian, Chayes, Jennifer T., Yaghi, Omar M.
The integration of artificial intelligence into scientific research has reached a new pinnacle with GPT-4V, a large language model featuring enhanced vision capabilities, accessible through ChatGPT or an API. This study demonstrates the remarkable ab
Externí odkaz:
http://arxiv.org/abs/2312.05468
Autor:
Zheng, Zhiling, Rong, Zichao, Rampal, Nakul, Borgs, Christian, Chayes, Jennifer T., Yaghi, Omar M.
Publikováno v:
Angew. Chem. Int. Ed. 2023, e202311983
We present a new framework integrating the AI model GPT-4 into the iterative process of reticular chemistry experimentation, leveraging a cooperative workflow of interaction between AI and a human researcher. This GPT-4 Reticular Chemist is an integr
Externí odkaz:
http://arxiv.org/abs/2306.14915
Publikováno v:
J. Am. Chem. Soc. 2023, 145, 32, 18048-18062
We use prompt engineering to guide ChatGPT in the automation of text mining of metal-organic frameworks (MOFs) synthesis conditions from diverse formats and styles of the scientific literature. This effectively mitigates ChatGPT's tendency to halluci
Externí odkaz:
http://arxiv.org/abs/2306.11296
Randomized experiments are widely used to estimate the causal effects of a proposed treatment in many areas of science, from medicine and healthcare to the physical and biological sciences, from the social sciences to engineering, to public policy an
Externí odkaz:
http://arxiv.org/abs/2205.12803
Kallenberg (2005) provided a necessary and sufficient condition for the local finiteness of a jointly exchangeable random measure on $\R_+^2$. Here we note an additional condition that was missing in Kallenberg's theorem, but was implicitly used in t
Externí odkaz:
http://arxiv.org/abs/1907.01613
We investigate structural properties of large, sparse random graphs through the lens of "sampling convergence" (Borgs et. al. (2017)). Sampling convergence generalizes left convergence to sparse graphs, and describes the limit in terms of a "graphex"
Externí odkaz:
http://arxiv.org/abs/1907.01605
In two recent papers by Veitch and Roy and by Borgs, Chayes, Cohn, and Holden, a new class of sparse random graph processes based on the concept of graphexes over $\sigma$-finite measure spaces has been introduced. In this paper, we introduce a metri
Externí odkaz:
http://arxiv.org/abs/1804.03277
Publikováno v:
Annals of Probability 47 (2019), no. 5, 2754-2800
Recent work has introduced sparse exchangeable graphs and the associated graphex framework, as a generalization of dense exchangeable graphs and the associated graphon framework. The development of this subject involves the interplay between the stat
Externí odkaz:
http://arxiv.org/abs/1708.03237
Autor:
Borgs, Christian, Chayes, Jennifer T.
Many social and economic systems are naturally represented as networks, from off-line and on-line social networks, to bipartite networks, like Netflix and Amazon, between consumers and products. Graphons, developed as limits of graphs, form a natural
Externí odkaz:
http://arxiv.org/abs/1706.01143