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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Filters: First Letter Of Last Name is W [Clear All Filters]

2017

Shen, W., Wang, B., Jiang, Y., Wang, Y. & Yuille, A. Multi-stage Multi-recursive-input Fully Convolutional Networks for Neuronal Boundary Detection. (2017).

CBMM-Memo-080.pdf (2.51 MB)

Shen, W., Wang, B., Jiang, Y., Wang, Y. & Yuille, A. Multi-stage Multi-recursive-input Fully Convolutional Networks for Neuronal Boundary Detection. (2017).

CBMM-Memo-080.pdf (2.51 MB)

Wu, Y., Muentener, P. & Schulz, L. One- to Four-year-olds’ Ability to Connect Diverse Positive Emotional Expressions to Their Probable Causes . Society for Research in Child Development (2017).

Deen, B. et al. Organization of high-level visual cortex in human infants. Nature Communications (2017). doi:10.1038/ncomms13995

Penagos, H., Varela, C. & Wilson, M. A. Oscillations, neural computations and learning during wake and sleep. Current Opinion in Neurobiology 44C, (2017).

Janner, M., Wu, J., Kulkarni, T., Yildirim, I. & Tenenbaum, J. B. Self-supervised intrinsic image decomposition. Annual Conference on Neural Information Processing Systems (NIPS) (2017). at <https://papers.nips.cc/paper/7175-self-supervised-intrinsic-image-decomposition>

intrinsicImg_nips_2017.pdf (5.87 MB)

zhang, zhoutong et al. Shape and Material from Sound. Advances in Neural Information Processing Systems 30 1278–1288 (2017). at <http://papers.nips.cc/paper/6727-shape-and-material-from-sound.pdf>

zhang, zhoutong et al. Shape and Material from Sound. Advances in Neural Information Processing Systems 30 1278–1288 (2017). at <http://papers.nips.cc/paper/6727-shape-and-material-from-sound.pdf>

Soltani, A. Arsalan, Huang, H., Wu, J., Kulkarni, T. & Tenenbaum, J. B. Synthesizing 3D Shapes via Modeling Multi-view Depth Maps and Silhouettes with Deep Generative Networks. 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2017). doi:10.1109/CVPR.2017.269

Synthesizing 3D Shapes via Modeling Multi-View Depth Maps and Silhouettes with Deep Generative Networks.pdf (2.86 MB)

Varela, C. & Wilson, M. A. Thalamic contribution to CA1-mPFC interactions during sleep. Society for Neuroscience's Annual Meeting - SfN 2017 (2017).

AbstractSFNfinal.docx (13.14 KB)

2018

Dehghani, N. & Wimmer, R. A computational perspective of the role of Thalamus in cognition. arxiv (2018). at <https://arxiv.org/abs/1803.00997>

ThalamusComputationArxiv.pdf (5.12 MB)

Adler, A. & Wax, M. Constant Modulus Algorithms via Low-Rank Approximation. (2018).

CBMM-Memo-077.pdf (795.61 KB)

Adler, A. & Wax, M. Constant Modulus Beamforming Via Low-Rank Approximation. 2018 IEEE Statistical Signal Processing Workshop (SSP) (2018). doi:10.1109/SSP.2018.8450799

Shen, W. et al. Deep Regression Forests for Age Estimation. (2018).

CBMM-Memo-085.pdf (2.2 MB)

Shen, W. et al. Deep Regression Forests for Age Estimation. (2018).

CBMM-Memo-085.pdf (2.2 MB)

Zhang, Z., Xie, C., Wang, J., Xie, L. & Yuille, A. DeepVoting: A Robust and Explainable Deep Network for Semantic Part Detection under Partial Occlusion. (2018).

CBMM-Memo-083.pdf (2.32 MB)

Zhang, Z., Xie, C., Wang, J., Xie, L. & Yuille, A. DeepVoting: An Explainable Framework for Semantic Part Detection under Partial Occlusion. Conference on Computer Vision and Pattern Recognition (CVPR) (2018). at <http://cvpr2018.thecvf.com/>

Wu, K., Wu, E. & Kreiman, G. Learning Scene Gist with Convolutional Neural Networks to Improve Object Recognition. arXiv | Cornell University arXiv:1803.01967, (2018).

Wu, K., Wu, E. & Kreiman, G. Learning Scene Gist with Convolutional Neural Networks to Improve Object Recognition. arXiv | Cornell University arXiv:1803.01967, (2018).

Wu, Y., Baker, C., Tenenbaum, J. B. & Schulz, L. Rational inference of beliefs and desires from emotional expressions. Cognitive Science 42, (2018).

Wu_Baker_Tenenbaum_Schulz_in_press_cognitive_science.pdf (1.65 MB)

Hu, S. et al. Real-Time Readout of Large-Scale Unsorted Neural Ensemble Place Codes. Cell Reports 25, 2635 - 2642.e5 (2018).

Wang, Y. - S., Liu, C., Zeng, X. & Yuille, A. Scene Graph Parsing as Dependency Parsing. (2018).

CBMM-Memo-082.pdf (869 KB)

Zhang, Z. et al. Single-Shot Object Detection with Enriched Semantics. Conference on Computer Vision and Pattern Recognition (CVPR) (2018). at <http://cvpr2018.thecvf.com/>

Zhang, Z. et al. Single-Shot Object Detection with Enriched Semantics. (2018).

CBMM-Memo-084.pdf (1.92 MB)

Tacchetti, A., Voinea, S. & Evangelopoulos, G. Trading robust representations for sample complexity through self-supervised visual experience. Advances in Neural Information Processing Systems 31 (Bengio, S. et al.) 9640–9650 (Curran Associates, Inc., 2018). at <http://papers.nips.cc/paper/8170-trading-robust-representations-for-sample-complexity-through-self-supervised-visual-experience.pdf>

trading-robust-representations-for-sample-complexity-through-self-supervised-visual-experience.pdf (3.32 MB)

NeurIPS2018_Poster.pdf (6.12 MB)

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