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2006 1
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2018 1
2021 0
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Accommodating space, time and randomness in network simulation.
Ridgway D, Broderick G, Ellison MJ. Ridgway D, et al. Curr Opin Biotechnol. 2006 Oct;17(5):493-8. doi: 10.1016/j.copbio.2006.08.004. Epub 2006 Sep 8. Curr Opin Biotechnol. 2006. PMID: 16962764 Review.
Interest in the possibility of dynamically simulating complex cellular processes has escalated markedly in recent years. ...Although at an early stage, methodological improvements and the development of computational platforms provide some hope that simulations will …
Interest in the possibility of dynamically simulating complex cellular processes has escalated markedly in recent years. ...Although …
A Theory of Sequence Indexing and Working Memory in Recurrent Neural Networks.
Frady EP, Kleyko D, Sommer FT. Frady EP, et al. Neural Comput. 2018 Jun;30(6):1449-1513. doi: 10.1162/neco_a_01084. Epub 2018 Apr 13. Neural Comput. 2018. PMID: 29652585
To accommodate structured approaches of neural computation, we propose a class of recurrent neural networks for indexing and storing sequences of symbols or analog data vectors. These networks with randomized input weights and orthogonal recurrent weig …
To accommodate structured approaches of neural computation, we propose a class of recurrent neural networks for indexing and s …
The role of collaborative interactivity in the observational practice of clinical skills.
Grierson LE, Barry M, Kapralos B, Carnahan H, Dubrowski A. Grierson LE, et al. Med Educ. 2012 Apr;46(4):409-16. doi: 10.1111/j.1365-2923.2011.04196.x. Med Educ. 2012. PMID: 22429177 Clinical Trial.
CONTEXT: Video-based observational practice can extend simulation-based learning outside the training space. This study explores the value of collaborative feedback provided during observational practice to the acquisition of clinical skills. ...The observation of a …
CONTEXT: Video-based observational practice can extend simulation-based learning outside the training space. This study explor …
A switching multi-scale dynamical network model of EEG/MEG.
Olier I, Trujillo-Barreto NJ, El-Deredy W. Olier I, et al. Neuroimage. 2013 Dec;83:262-87. doi: 10.1016/j.neuroimage.2013.04.046. Epub 2013 Apr 21. Neuroimage. 2013. PMID: 23611860
Additionally, four generalising assumptions are now included: (4) the mesostates interact according to a full Dynamical Causal Network (DCN) that can be estimated; (5) the dynamics of the mesostates can switch between multiple approximately linear operating regimes; (6) ea …
Additionally, four generalising assumptions are now included: (4) the mesostates interact according to a full Dynamical Causal Network
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