Publication

Found 906 results
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D
Dehghani, N. Design of the Artificial: lessons from the biological roots of general intelligence. (2017). at <https://arxiv.org/pdf/1703.02245>PDF icon DesignArtificial_Dehghani_arXiv.pdf (222.47 KB)
A del Molino, G., Boix, X., Lim, J. & Tan, A. Active Video Summarization: Customized Summaries via On-line Interaction. AAAI Conference on Artificial Intelligence (2017).PDF icon 21-Garcia-del-Molino-14856.pdf (413.77 KB)
Dellaferrera, G. & Kreiman, G. Error-driven Input Modulation: Solving the Credit Assignment Problem without a Backward Pass. Proceedings of the 39th International Conference on Machine Learning, PMLR 162, 4937-4955 (2022).PDF icon dellaferrera22a.pdf (909.91 KB)
Deza, A., Liao, Q., Banburski, A. & Poggio, T. Hierarchically Local Tasks and Deep Convolutional Networks. (2020).PDF icon CBMM_Memo_109.pdf (2.12 MB)
Dillon, M. R. & Spelke, E. S. From Map Reading to Geometric Intuitions. Developmental Psychology (2018). doi:http://dx.doi.org/10.1037/dev0000509
Dillon, M. R. & Spelke, E. S. Reorientation ability predicts early spatial symbol reading. 2015 Society for Research in Child Development Biennial Meeting (2015).
Dillon, M. R. & Spelke, E. S. Young children's use of distance and angle information during map reading. SRCD (2017).
Dillon, M. R. & Spelke, E. S. Connecting core cognition, spatial symbols, and the abstract concepts of formal geometry. Cognitive Development Society Post-Conference, More on Development (2015).
Dillon, M. R. & Spelke, E. S. Young children’s automatic and alternating use of scene and object information in spatial symbols. Budapest CEU Conference on Cognitive Development (2015).
Dillon, M. R., Pires, A. C., Hyde, D. C. & Spelke, E. S. Children's expectations about training the approximate number system. British Journal of Developmental Psychology 33, (2015).
Dillon, M. R. & Spelke, E. S. From spatial symbols to Euclidean intuitions. Cognitive Development Society (CDS) (2015). at <http://cogdevsoc.org/sites/default/files/Official%20Full%20Conference%20Proceedings_10.10.pdf>
Dillon, M. R., Izard, V. & Spelke, E. S. Isolating angle in infants' detection of shape. (2015).PDF icon SRCD_2015_Dillonetal.pdf (5.01 MB)
Dillon, M. R. & Spelke, E. S. Young Children’s Use of Surface and Object Information in Drawings of Everyday Scenes. Child Development (2016). doi:10.1111/cdev.12658
Dillon, M. R., Izard, V. & Spelke, E. S. Infants’ sensitivity to shape changes. Cognitive Development Society Pre-Conference on the Development of Spatial Thinking (2015).
Dillon, M. R., Izard, V. & Spelke, E. S. Infants’ sensitivity to shape changes in 2D visual forms. Infancy 25, 618 - 639 (2020).
Dillon, M. R. & Spelke, E. S. Core geometry in perspective. Developmental Science (2014). doi:10.1111/desc.12266
Dillon, M. R. & Spelke, E. S. Spatial cognition across development. SRCD (2017).
Dillon, M. R., Huang, Y. & Spelke, E. S. Core foundations of abstract geometry. Proceedings of National Academy of Sciences of the United States of America 110, (2013).
Dillon, M. R. & Spelke, E. S. From spatial symbols to Euclidean intuitions. Biennial Meeting of Cognitive Development Society (2015).
Dobs, K., Kell, A. J. E., Martinez-Trujillo, J., Cohen, M. & Kanwisher, N. Using task-optimized neural networks to understand why brains have specialized processing for faces . Computational and Systems Neurosciences (2020).
Dobs, K., Yuan, J., Martinez, J. & Kanwisher, N. Behavioral signatures of face perception emerge in deep neural networks optimized for face recognition. Proceedings of the National Academy of Sciences 120, (2023).
Dobs, K., Kell, A. J. E., Martinez-Trujillo, J., Cohen, M. & Kanwisher, N. Why Are Face and Object Processing Segregated in the Human Brain? Testing Computational Hypotheses with Deep Convolutional Neural Networks . Conference on Cognitive Computational Neuroscience (2020).
Dobs, K., Isik, L., Pantazis, D. & Kanwisher, N. How face perception unfolds over time. Nature Communications 10, (2019).
Dobs, K. et al. Effects of Face Familiarity in Humans and Deep Neural Networks . European Conference on Visual Perception (2019).
Dobs, K., Martinez-Trujillo, J., Kell, A. J. E. & Kanwisher, N. Brain-like functional specialization emerges spontaneously in deep neural networks. Science Advances 8, (2022).

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