Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Tomi Peltola"'
Autor:
Dmitry Smirnov, Fanny Lachat, Tomi Peltola, Juha M Lahnakoski, Olli-Pekka Koistinen, Enrico Glerean, Aki Vehtari, Riitta Hari, Mikko Sams, Lauri Nummenmaa
Publikováno v:
PLoS ONE, Vol 12, Iss 12, p e0189508 (2017)
Seeing an action may activate the corresponding action motor code in the observer. It remains unresolved whether seeing and performing an action activates similar action-specific motor codes in the observer and the actor. We used novel hyperclassific
Externí odkaz:
https://doaj.org/article/ecc213f33f4f47509c50311db39b4af4
Publikováno v:
PLoS ONE, Vol 7, Iss 1, p e29115 (2012)
Although complex diseases and traits are thought to have multifactorial genetic basis, the common methods in genome-wide association analyses test each variant for association independent of the others. This computational simplification may lead to r
Externí odkaz:
https://doaj.org/article/8b80db146b424272a4dd3ff560ccf6b8
Publikováno v:
PLoS ONE, Vol 7, Iss 11, p e49445 (2012)
High-dimensional datasets with large amounts of redundant information are nowadays available for hypothesis-free exploration of scientific questions. A particular case is genome-wide association analysis, where variations in the genome are searched f
Externí odkaz:
https://doaj.org/article/8efcae0b4b0d443e97eddfd55cc60276
Publikováno v:
Afrabandpey, H, Peltola, T, Piironen, J, Vehtari, A & Kaski, S 2020, ' A decision-theoretic approach for model interpretability in Bayesian framework ', Machine Learning, vol. 109, no. 9-10, pp. 1855-1876 . https://doi.org/10.1007/s10994-020-05901-8
A salient approach to interpretable machine learning is to restrict modeling to simple models. In the Bayesian framework, this can be pursued by restricting the model structure and prior to favor interpretable models. Fundamentally, however, interpre
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::041b289f887ea84d6acf8154c2bdfee4
https://aaltodoc.aalto.fi/handle/123456789/46824
https://aaltodoc.aalto.fi/handle/123456789/46824
Autor:
Tomi Peltola, Paul Blomstedt, Paul Whaley, Barbara Raffael, Maurice Whelan, John Paul Gosling, Clemens Wittwehr, Marta Sienkiewicz, Andrea-Nicole Richarz, Andrew Worth
Publikováno v:
Computational Toxicology (Amsterdam, Netherlands)
Highlights • Artificial Intelligence (AI) has potential to improve chemical risk assessment (CRA) and associated regulatory decisions. • AI could influence the scientific-technical evaluation process and the social aspects of the CRA decision mak
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aedcb86a45b4fe80033ad2e0ff83dc85
https://aaltodoc.aalto.fi/handle/123456789/101567
https://aaltodoc.aalto.fi/handle/123456789/101567
Autor:
Tomi Peltola, Minna L. Hannuksela, Sanna Kuusisto, Markku J. Savolainen, Maria Laitinen, Linda S. Kumpula, Ville-Petteri Mäkinen, Matti Jauhiainen, Tuire Salonurmi, Pirjo Hedberg, Mika Ala-Korpela
Context and objective. Lipoproteins are involved in the pathophysiology of several metabolic diseases. Here we focus on the interplay between lipoprotein metabolism and adiponectin with the extension of alcohol intake. Design and subjects. Eighty-thr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b287732566c36e497cd8b5a9b27d7ee8
Publikováno v:
Scientific Reports, Vol 8, Iss 1, Pp 1-13 (2018)
Scientific Reports
Scientific Reports
In metazoans, epithelial architecture provides a context that dynamically modulates most if not all epithelial cell responses to intrinsic and extrinsic signals, including growth or survival signalling and transforming oncogene action. Three-dimensio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cb08da81887ee856e8f2f37610e7373f
http://link.springer.com/article/10.1038/s41598-018-22293-x
http://link.springer.com/article/10.1038/s41598-018-22293-x
Publikováno v:
IJCAI
Learning predictive models from small high-dimensional data sets is a key problem in high-dimensional statistics. Expert knowledge elicitation can help, and a strong line of work focuses on directly eliciting informative prior distributions for param
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b4fe9cbe0bdbac1da4e66f1402c6ca4c
https://doi.org/10.24963/ijcai.2019/271
https://doi.org/10.24963/ijcai.2019/271
Autor:
Fanny Lachat, Juha M. Lahnakoski, Riitta Hari, Aki Vehtari, Tomi Peltola, Enrico Glerean, Dmitry Smirnov, Lauri Nummenmaa, Mikko Sams, Olli-Pekka Koistinen
Publikováno v:
PLoS ONE
PLoS ONE, Vol 12, Iss 12, p e0189508 (2017)
PLoS ONE, Vol 12, Iss 12, p e0189508 (2017)
Seeing an action may activate the corresponding action motor code in the observer. It remains unresolved whether seeing and performing an action activates similar action-specific motor codes in the observer and the actor. We used novel hyperclassific
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bcce37cb80ae893bc64168db21512372
https://pubmed.ncbi.nlm.nih.gov/29228054
https://pubmed.ncbi.nlm.nih.gov/29228054
Regression under the "small $n$, large $p$" conditions, of small sample size $n$ and large number of features $p$ in the learning data set, is a recurring setting in which learning from data is difficult. With prior knowledge about relationships of t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f99d743ac1145e62cbf6248b297fa519
http://arxiv.org/abs/1612.02802
http://arxiv.org/abs/1612.02802