Francisco Pereira, Ph.D.

Affiliations: 
Siemens Healthcare 
Area:
machine learning
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"Francisco Pereira"
Mean distance: 15.56 (cluster 15)
 
SNBCP
Cross-listing: Computer Science Tree

Parents

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Tom Michael Mitchell grad student 2007 Carnegie Mellon
 (Beyond brain blobs: Machine learning classifiers as instruments for analyzing functional magnetic resonance imaging data.)
Matthew M. Botvinick post-doc Princeton
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Publications

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Gonzalez-Castillo J, Caballero-Gaudes C, Topolski N, et al. (2019) Imaging the spontaneous flow of thought: Distinct periods of cognition contribute to dynamic functional connectivity during rest. Neuroimage. 116129
Pereira F, Lou B, Pritchett B, et al. (2018) Toward a universal decoder of linguistic meaning from brain activation. Nature Communications. 9: 963
Pereira F, Gershman S, Ritter S, et al. (2016) A comparative evaluation of off-the-shelf distributed semantic representations for modelling behavioural data. Cognitive Neuropsychology. 33: 175-90
Pereira F, Botvinick M, Detre G. (2013) Using Wikipedia to learn semantic feature representations of concrete concepts in neuroimaging experiments. Artificial Intelligence. 194: 240-252
Pereira F, Botvinick M. (2013) Simitar: Simplified searching of statistically significant similarity structure Proceedings - 2013 3rd International Workshop On Pattern Recognition in Neuroimaging, Prni 2013. 1-4
Allen K, Pereira F, Botvinick M, et al. (2012) Distinguishing grammatical constructions with fMRI pattern analysis. Brain and Language. 123: 174-82
Pereira F, Botvinick M. (2012) A systematic approach to extracting semantic information from functional MRI data Advances in Neural Information Processing Systems. 3: 2267-2275
Pereira F, Detre G, Botvinick M. (2011) Generating text from functional brain images. Frontiers in Human Neuroscience. 5: 72
Gershman SJ, Blei DM, Pereira F, et al. (2011) A topographic latent source model for fMRI data. Neuroimage. 57: 89-100
Pereira F, Botvinick M. (2011) Information mapping with pattern classifiers: A comparative study Neuroimage. 56: 476-496
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