Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Ellyn Ayton"'
Publikováno v:
PLoS ONE, Vol 12, Iss 12, p e0188941 (2017)
This work is the first to take advantage of recurrent neural networks to predict influenza-like illness (ILI) dynamics from various linguistic signals extracted from social media data. Unlike other approaches that rely on timeseries analysis of histo
Externí odkaz:
https://doaj.org/article/422b930cb3f34317aaaaa4d15ca834c1
Autor:
Maria Glenski, Ellyn Ayton, Sannisth Soni, Emily Saldanha, Dustin Arendt, Brian Quiter, Ren Cooper, Svitlana Volkova
Publikováno v:
IEEE Transactions on Nuclear Science. 69:1375-1384
Autor:
Sinan Aksoy, Brett Jefferson, Ellyn Ayton, Svitlana Volkova, Dustin Arendt, Karthnik Shrivaram, Joseph Cottam, Emily Saldanha, Maria Glenski
Publikováno v:
Computational and Mathematical Organization Theory. 29:220-241
Ground Truth program was designed to evaluate social science modeling approaches using simulation test beds with ground truth intentionally and systematically embedded to understand and model complex Human Domain systems and their dynamics Lazer et a
Publikováno v:
SocialNLP@NAACL
With the increasing use of machine-learning driven algorithmic judgements, it is critical to develop models that are robust to evolving or manipulated inputs. We propose an extensive analysis of model robustness against linguistic variation in the se
Publikováno v:
Proceedings of the Fourth Workshop on NLP for Internet Freedom: Censorship, Disinformation, and Propaganda.
Deceptive news posts shared in online communities can be detected with NLP models, and much recent research has focused on the development of such models. In this work, we use characteristics of online communities and authors -- the context of how an
Evaluation beyond aggregate performance metrics, e.g. F1-score, is crucial to both establish an appropriate level of trust in machine learning models and identify future model improvements. In this paper we demonstrate CrossCheck, an interactive visu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7eb63fc8d4aba84750f33d65bd5fdb13
http://arxiv.org/abs/2004.07993
http://arxiv.org/abs/2004.07993
Publikováno v:
IJCNN
Despite the explosion of craft beer brewing over the last decade, there is virtually no work in the public domain exploring machine learning approaches to understand and optimize the brewing process. Learning to map between representations of an obje
Publikováno v:
PLoS ONE, Vol 12, Iss 12, p e0188941 (2017)
PLoS ONE
PLoS ONE
This work is the first to take advantage of recurrent neural networks to predict influenza-like illness (ILI) dynamics from various linguistic signals extracted from social media data. Unlike other approaches that rely on timeseries analysis of histo