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Representation of cognitive processes using the minimum spanning tree of local meshes.

, , , , and . EMBC, page 6780-6783. IEEE, (2013)

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Mesh learning for object classification using fMRI measurements., , , , , and . ICIP, page 2631-2634. IEEE, (2013)Functional Mesh Learning for pattern analysis of cognitive processes., , , , and . ICCI*CC, page 161-167. IEEE Computer Society, (2013)Information distribution analysis in the fMRI measurements with degree of locality estimation., , , , and . SIU, page 1-4. IEEE, (2013)Cognitive process representation with minimum spanning tree of local meshes., , , , and . SIU, page 1-4. IEEE, (2013)An information theoretic approach to classify cognitive states using fMRI., , , , and . BIBE, page 1-6. IEEE Computer Society, (2013)Modeling the Sequence of Brain Volumes by Local Mesh Models for Brain Decoding., , , , and . CoRR, (2016)Learning Deep Temporal Representations for fMRI Brain Decoding., , , and . MLMMI@ICML, volume 9487 of Lecture Notes in Computer Science, page 25-34. Springer, (2015)Enhancing Local Linear Models Using Functional Connectivity for Brain State Decoding., , , , and . IJCINI, 7 (3): 46-57 (2013)Analyzing the information distribution in the fMRI measurements by estimating the degree of locality., , , , and . EMBC, page 6772-6775. IEEE, (2013)Decoding cognitive states using the bag of words model on fMRI time series., , , , and . SIU, page 2245-2248. IEEE, (2016)