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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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Ziyin, L., Chuang, I., Galanti, T. & Poggio, T. Formation of Representations in Neural Networks. (2024).

CBMM-Memo-150.pdf (4.03 MB)

Zisselman, E., Adler, A. & Elad, M. Handbook of Numerical Analysis 19, 3 - 17 (Elsevier, 2018).

Zhou, L., Smith, K., Tenenbaum, J. B. & Gerstenberg, T. Mental Jenga: A counterfactual simulation model of causal judgments about physical support. PsyArXiv (2022). at <https://psyarxiv.com/4a5uh>

Zheng, J. et al. Cognitive boundary signals in the human medial temporal lobe shape episodic memory representation. bioRxiv (2021).

Zheng, J. et al. Neurons detect cognitive boundaries to structure episodic memories in humans. Nature Neuroscience 25, 358 - 368 (2022).

Zhang, M. et al. Look twice: A generalist computational model predicts return fixations across tasks and species. PLOS Computational Biology 18, e1010654 (2022).

journal.pcbi_.1010654.pdf (4.51 MB)

Zhang, M., Feng, J., Lim, J. Hwee, Zhao, Q. & Kreiman, G. What am I searching for?. (2018).

CBMM-Memo-096.pdf (1.74 MB)

Zhang, Y., Marciniak, K. & Freiwald, W. A. Analysis of Macaque Monkeys’ Social and Physical Interaction Processing with Eye tracking Data. The Rockefeller University 2019 Summer Science Research Program (SSRP) (2019).

Zhang, Y. et al. Decoding of human identity by computer vision and neuronal vision. Scientific Reports 13, (2023).

s41598-022-26946-w.pdf (1.88 MB)

Zhang, C., Voinea, S., Evangelopoulos, G., Rosasco, L. & Poggio, T. Discriminative Template Learning in Group-Convolutional Networks for Invariant Speech Representations. INTERSPEECH-2015 (International Speech Communication Association (ISCA), 2015). at <http://www.isca-speech.org/archive/interspeech_2015/i15_3229.html>

Zhang, M. & Kreiman, G. Beauty is in the eye of the machine. Nature Human Behaviour 5, 675 - 676 (2021).

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, C., Evangelopoulos, G., Voinea, S., Rosasco, L. & Poggio, T. A Deep Representation for Invariance And Music Classification. (2014).

CBMM-Memo-002.pdf (1.63 MB)

Zhang, M., Tseng, C. & Kreiman, G. Putting visual object recognition in context. CVPR 2020 (2020).

gk7876.pdf (3.12 MB)

Zhang, Z. et al. Generative modeling of audible shapes for object perception. The IEEE International Conference on Computer Vision (ICCV) (2017). at <http://openaccess.thecvf.com/content_iccv_2017/html/Zhang_Generative_Modeling_of_ICCV_2017_paper.html>

Zhang, C. et al. Theory of Deep Learning IIb: Optimization Properties of SGD. (2017).

CBMM-Memo-072.pdf (3.66 MB)

Zhang, C., Evangelopoulos, G., Voinea, S., Rosasco, L. & Poggio, T. A Deep Representation for Invariance and Music Classification. ICASSP 2014 - 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (IEEE, 2014). doi:10.1109/ICASSP.2014.6854954

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

CBMM-Memo-084.pdf (1.92 MB)

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, C. et al. Musings on Deep Learning: Properties of SGD. (2017).

CBMM Memo 067 v2 (revised 7/19/2017) (5.88 MB)

CBMM Memo 067 v3 (revised 9/15/2017) (5.89 MB)

CBMM Memo 067 v4 (revised 12/26/2017) (5.57 MB)

Zhang, M., Badkundri, R., Talbot, M. B., Zawar, R. & Kreiman, G. Hypothesis-driven Online Video Stream Learning with Augmented Memory. arXiv (2021). doi:10.48550/arXiv.2104.02206

2104.02206.pdf (2.25 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, C., Frogner, C., Araya-Polo, M. & Hohl, D. Machine Learning Based Automated Fault Detection in Seismic Traces. EAGE Conference and Exhibition 2014 (2014). at <http://cbcl.mit.edu/publications/eage14.pdf>

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/>

Zhang, M. et al. Finding any Waldo with zero-shot invariant and efficient visual search. Nature Communications 9, (2018).

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