Zobrazeno 1 - 10
of 323
pro vyhledávání: '"Fernando Perez-cruz"'
Publikováno v:
Scientific Data, Vol 10, Iss 1, Pp 1-20 (2023)
Abstract The use of machine learning for predicting ecotoxicological outcomes is promising, but underutilized. The curation of data with informative features requires both expertise in machine learning as well as a strong biological and ecotoxicologi
Externí odkaz:
https://doaj.org/article/94727c1144ae4964a6c9a9436b41f898
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-13 (2022)
Abstract Type 2 diabetes mellitus (T2DM) is associated with the development of chronic comorbidities, which can lead to high drug utilization and adverse events. We aimed to identify common comorbidity clusters and explore the progression over time i
Externí odkaz:
https://doaj.org/article/f788b9f6e961429399c767e9d3dd4571
Autor:
Melanie F. Pradier, Bernhard Reis, Lori Jukofsky, Francesca Milletti, Toshihiko Ohtomo, Fernando Perez-Cruz, Oscar Puig
Publikováno v:
BMC Cancer, Vol 19, Iss 1, Pp 1-7 (2019)
Abstract Background Codrituzumab, a humanized monoclonal antibody against Glypican-3 (GPC3), which is expressed in hepatocellular carcinoma (HCC), was tested in a randomized phase II trial in advanced HCC patients who had failed prior systemic therap
Externí odkaz:
https://doaj.org/article/c84e3057b2a241b69d2832c6f9702481
Publikováno v:
SciPost Physics Core, Vol 5, Iss 3, p 043 (2022)
For stochastic models with intractable likelihood functions, approximate Bayesian computation offers a way of approximating the true posterior through repeated comparisons of observations with simulated model outputs in terms of a small set of sum
Externí odkaz:
https://doaj.org/article/50aeffde2edc466a96863508847d68ef
GIR dataset: A geometry and real impulse response dataset for machine learning research in acoustics
Autor:
Achilleas Xydis, Nathanaël Perraudin, Romana Rust, Kurt Heutschi, Gonzalo Casas, Oksana Riba Grognuz, Kurt Eggenschwiler, Matthias Kohler, Fernando Perez-Cruz
Publikováno v:
Applied Acoustics, 208
Acoustics play a significant role in our everyday lives, influencing our communication, well-being, and perception of space. Fast and precise acoustics simulation is crucial for the accurate design of real spaces by architects and acousticians and ma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::777a755a6663b1c6eccbe27a73e133e8
https://hdl.handle.net/20.500.11850/610930
https://hdl.handle.net/20.500.11850/610930
The use of machine learning for predicting ecotoxicological outcomes is promising, but underutilized. The curation of data with informative features requires both expertise in machine learning as well as a strong biological and ecotoxicological backg
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f345e3eb66aed301dbe4ac76c8f8e4cf
https://doi.org/10.1101/2023.05.27.542160
https://doi.org/10.1101/2023.05.27.542160
Autor:
Sichen Li, Mélissa Zacharias, Jochem Snuverink, Jaime Coello de Portugal, Fernando Perez-Cruz, Davide Reggiani, Andreas Adelmann
Publikováno v:
Information, Vol 12, Iss 3, p 121 (2021)
The beam interruptions (interlocks) of particle accelerators, despite being necessary safety measures, lead to abrupt operational changes and a substantial loss of beam time. A novel time series classification approach is applied to decrease beam tim
Externí odkaz:
https://doaj.org/article/457e13c0b2a7457d9d59c9c4a105302e
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783031264184
Lecture Notes in Computer Science, 13717
Machine Learning and Knowledge Discovery in Databases
Lecture Notes in Computer Science, 13717
Machine Learning and Knowledge Discovery in Databases
Annealed Importance Sampling (AIS) is a popular algorithm used to estimates the intractable marginal likelihood of deep generative models. Although AIS is guaranteed to provide unbiased estimate for any set of hyperparameters, the common implementati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c4d868d30ca64aa5194cb3f516bbfc5a
https://doi.org/10.1007/978-3-031-26419-1_11
https://doi.org/10.1007/978-3-031-26419-1_11
Publikováno v:
PLoS ONE, Vol 13, Iss 8, p e0200822 (2018)
Economic complexity reflects the amount of knowledge that is embedded in the productive structure of an economy. It resides on the premise of hidden capabilities-fundamental endowments underlying the productive structure. In general, measuring the ca
Externí odkaz:
https://doaj.org/article/a51b9188ce9644409249aa00e8fc809b
Publikováno v:
Information Sciences. 637:118928
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::63bd96ad3879f222f5bb4b5448272b28
https://doi.org/10.1016/j.ins.2023.04.007
https://doi.org/10.1016/j.ins.2023.04.007