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

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

CBMM-Memo-096.pdf (1.74 MB)

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, 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, J., Han, Y., Poggio, T. & Roig, G. Eccentricity Dependent Neural Network with Recurrent Attention for Scale, Translation and Clutter Invariance . Vision Science Society (2019).

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, 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. Phone Classification by a Hierarchy of Invariant Representation Layers. INTERSPEECH 2014 - 15th Annual Conf. of the International Speech Communication Association (International Speech Communication Association (ISCA), 2014). at <http://www.isca-speech.org/archive/interspeech_2014/i14_2346.html>

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

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

CBMM-Memo-084.pdf (1.92 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, 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. Theory of Deep Learning IIb: Optimization Properties of SGD. (2017).

CBMM-Memo-072.pdf (3.66 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/>

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

gk7876.pdf (3.12 MB)

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

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>

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