Publications

CBMM Memos were established in 2014 as a mechanism for our center to share research results with the wider scientific community. Click here to read more about the memos and to see a full list of the memos.

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Found 129 results

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2013

Lattman, E., Poggio, T. & Westervelt, R. NSF Science and Technology Centers – The Class of 2013. (2013).

NSFGender2013_poster.pdf (2.77 MB)

2014

Amir, N. et al. Abstracts of the 2014 Brains, Minds, and Machines Summer Course. (2014).

CBMM-Memo-024.pdf (2.86 MB)

Amir, N. et al. Abstracts of the 2014 Brains, Minds, and Machines Summer Course. (2014).

CBMM-Memo-024.pdf (2.86 MB)

Barbu, A. et al. The Compositional Nature of Event Representations in the Human Brain. (2014).

CBMM Memo 011.pdf (3.95 MB)

Winston, P. Henry. The Genesis Story Understanding and Story Telling System A 21st Century Step toward Artificial Intelligence. (2014).

CBMM-Memo-019_StoryWhitePaper.pdf (894.38 KB)

Linderman, S. W., Johnson, M. J., Wilson, M. A. & Chen, Z. A Nonparametric Bayesian Approach to Uncovering Rat Hippocampal Population Codes During Spatial Navigation. (2014).

CBMM-Memo-027.pdf (9.44 MB)

Xu, J., Jiang, M., Wang, S., Kankanhalli, M. & Zhao, Q. Predicting Saliency Beyond Pixels. (2014). at <http://www.ece.nus.edu.sg/stfpage/eleqiz/predicting.html>

Wang, C., Wang, Y., Lin, Z., Yuille, A. & Gao, W. Robust Estimation of 3D Human Poses from a Single Image. (2014).

CBMM-Memo-013.pdf (510.23 KB)

Wang, C., Wang, Y., Lin, Z., Yuille, A. & Gao, W. Robust Estimation of 3D Human Poses from a Single Image. (2014).

CBMM-Memo-013.pdf (510.23 KB)

Barbu, A. et al. Seeing is Worse than Believing: Reading People’s Minds Better than Computer-Vision Methods Recognize Actions. (2014).

CBMM Memo 012.pdf (678.95 KB)

Barbu, A. et al. Computer Vision – ECCV 2014, Lecture Notes in Computer Science 8693, 612–627 (Springer International Publishing, 2014).

Prevedel, R. et al. Simultaneous whole-animal 3D imaging of neuronal activity using light-field microscopy. Nature Methods 11, 727 - 730 (2014).

2015

Mao, J. et al. Deep Captioning with Multimodal Recurrent Neural Networks (m-RNN). (2015).

CBMM Memo 033.pdf (839.42 KB)

Wu, Y. & Schulz, L. A fine-grained understanding of emotions: Young children match within-valence emotional expressions to their causes. Cognitive Science Conference (CogSci) 2685-2690 (2015).

Cogsci Emotion pairings 2-4-15 Final version.pdf (729.07 KB)

Wu, J., Yildirim, I., Lim, J. J., Freeman, W. T. & Tenenbaum, J. B. Galileo: Perceiving physical object properties by integrating a physics engine with deep learning. NIPS 2015 (2015). at <https://papers.nips.cc/paper/5780-galileo-perceiving-physical-object-properties-by-integrating-a-physics-engine-with-deep-learning>

Mao, J. et al. Learning like a Child: Fast Novel Visual Concept Learning from Sentence Descriptions of Images. International Conference of Computer Vision (2015). at <www.stat.ucla.edu/~junhua.mao/projects/child_learning.html>

child_learning_iccv2015.pdf (1.16 MB)

Winston, P. Henry. Model-based Story Summary. 6th Workshop on Computational Models of Narrative (2015). doi:10.4230/OASIcs.CMN.2015.157

Wong, A. & Yuille, A. One Shot Learning by Composition of Meaningful Patches. International Conference on Computer Vision (ICCV) (2015).

AlexWongOneShotCVPR2015.pdf (1.83 MB)

Wong, A. & Yuille, A. One Shot Learning via Compositions of Meaningful Patches. International Conference on Computer Vision (ICCV) (2015).

AlexWongOneShotCVPR2015.pdf (1.83 MB)

Newman, J. P. et al. Optogenetic feedback control of neural activity. Elife 4, e07192 (2015).

elife-07192-v1-download.pdf (5.92 MB)

Buice, M. & de Vries, S. Population Coding, Correlations, and Functional Connectivity in the mouse visual system with the Cortical Activity Map (CAM). Society for Neuroscience 2015 (2015).

2015 SFN Population_Coding.pdf (2.94 MB)

Buice, M. & de Vries, S. Population Coding, Correlations, and Functional Connectivity in the mouse visual system with the Cortical Activity Map (CAM). Society for Neuroscience 2015 (2015).

2015 SFN Population_Coding.pdf (2.94 MB)

Buice, M. & de Vries, S. Population Coding, Correlations, and Functional Connectivity in the mouse visual system with the Cortical Activity Map (CAM). Society for Neuroscience 2015 (2015).

2015 SFN Population_Coding.pdf (2.94 MB)

Buice, M. & de Vries, S. Population Coding, Correlations, and Functional Connectivity in the mouse visual system with the Cortical Activity Map (CAM). Society for Neuroscience 2015 (2015).

2015 SFN Population_Coding.pdf (2.94 MB)

Ren, Z., Wang, C. & Yuille, A. Scene-Domain Active Part Models for Object Representation. IEEE International Conference on Computer Vision (ICCV) 2497 - 2505 (2015). doi:10.1109/ICCV.2015.287

Ren_ICCV15.pdf (3.37 MB)

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