Zobrazeno 1 - 10
of 92
pro vyhledávání: '"Manuel Gomez Rodriguez"'
Autor:
Isobel Routledge, José Eduardo Romero Chevéz, Zulma M. Cucunubá, Manuel Gomez Rodriguez, Caterina Guinovart, Kyle B. Gustafson, Kammerle Schneider, Patrick G.T. Walker, Azra C. Ghani, Samir Bhatt
Publikováno v:
Nature Communications, Vol 9, Iss 1, Pp 1-8 (2018)
Twenty one countries have been identified for malaria elimination by 2020 and their progress needs to be constantly evaluated. Here, the authors present a method that estimates individual reproduction numbers and their variation through time and spac
Externí odkaz:
https://doaj.org/article/1c21344e393940af868c7c0c26f68539
Autor:
Gilles Barthe, Roberta De Viti, Peter Druschel, Deepak Garg, Manuel Gomez-Rodriguez, Pierfrancesco Ingo, Heiner Kremer, Matthew Lentz, Lars Lorch, Aastha Mehta, Bernhard Schölkopf
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-14 (2022)
Abstract The ongoing COVID-19 pandemic let to efforts to develop and deploy digital contact tracing systems to expedite contact tracing and risk notification. Unfortunately, the success of these systems has been limited, partly owing to poor interope
Externí odkaz:
https://doaj.org/article/6209c59bb629427da0de478e32e04d32
Publikováno v:
PLoS Computational Biology, Vol 18, Iss 3, p e1010008 (2022)
Testing is recommended for all close contacts of confirmed COVID-19 patients. However, existing pooled testing methods are oblivious to the circumstances of contagion provided by contact tracing. Here, we build upon a well-known semi-adaptive pooled
Externí odkaz:
https://doaj.org/article/a91027863d284a30b30fa48967d15af0
Publikováno v:
ACM Transactions on Information Systems
Social media is an attention economy where broadcasters are constantly competing for attention in their followers’ feeds. Broadcasters are likely to elicit greater attention from their followers if their posts remain visible at the top of their fol
Publikováno v:
AAAI
Decisions are increasingly taken by both humans and machine learning models. However, machine learning models are currently trained for full automation—they are not aware that some of the decisions may still be taken by humans. In this paper, we ta
Autor:
Roberta De Viti, Peter Druschel, Heiner Kremer, Gilles Barthe, Aastha Mehta, Pierfrancesco Ingo, Lars Lorch, Matthew Lentz, Manuel Gomez Rodriguez, Bernhard Schoelkopf, Deepak Garg
Publikováno v:
Scientific Reports, 12
The ongoing COVID-19 pandemic let to efforts to develop and deploy digital contact tracing systems to expedite contact tracing and risk notification. Unfortunately, the success of these systems has been limited, partly owing to poor interoperability
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e3ed0b00b6d6ea119a9f66e5999b4ce9
Publikováno v:
NPJ Science of Learning
npj Science of Learning, Vol 6, Iss 1, Pp 1-3 (2021)
npj Science of Learning, Vol 6, Iss 1, Pp 1-3 (2021)
We perform a large-scale randomized controlled trial to evaluate the potential of machine learning-based instruction sequencing to improve memorization while allowing the learners the freedom to choose their review times. After controlling for the le
Autor:
Bidisha Samanta, Manuel Gomez Rodriguez, Abir De, Gourhari Jana, Pratim Kumar Chattaraj, Niloy Ganguly
Publikováno v:
AAAI
Scopus-Elsevier
Scopus-Elsevier
Deep generative models have been praised for their ability to learn smooth latent representation of images, text, and audio, which can then be used to generate new, plausible data. However, current generative models are unable to work with molecular
Autor:
Manuel Gomez-Rodriguez, Ali Zarezade, Abir De, Utkarsh Upadhyay, Behzad Tabibian, Bernhard Schölkopf
Publikováno v:
Proceedings of the National Academy of Sciences. 116:3988-3993
Spaced repetition is a technique for efficient memorization which uses repeated review of content following a schedule determined by a spaced repetition algorithm to improve long-term retention. However, current spaced repetition algorithms are simpl
The multi-volume set LNAI 14169 until 14175 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2023, which took place in Turin, Italy, in September 2023.The 196 papers w