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 910 results

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CBMM Memos

Dehaene-Lambertz, G. & Spelke, E. S. The infancy of the human brain. (2016). doi:http://dx.doi.org/10.1016/j.neuron.2015.09.026

CBMM-Memo-053.pdf (1.51 MB)

Anselmi, F., Rosasco, L. & Poggio, T. On Invariance and Selectivity in Representation Learning. (2015).

CBMM Memo No. 029 (812.07 KB)

Leibo, J. Z., Liao, Q., Anselmi, F. & Poggio, T. The Invariance Hypothesis Implies Domain-Specific Regions in Visual Cortex. (2014). doi:10.1101/004473

CBMM Memo 004_new.pdf (2.25 MB)

Poggio, T., Anselmi, F. & Rosasco, L. I-theory on depth vs width: hierarchical function composition. (2015).

cbmm_memo_041.pdf (1.18 MB)

Xu, M. et al. The Janus effects of SGD vs GD: high noise and low rank. (2023).

Updated with appendix showing empirically that the main results extend to deep nonlinear networks (2.95 MB)

Small updates...typos... (616.82 KB)

Wang, C., Ross, C., Kuo, Y. - L., Katz, B. & Barbu, A. Learning a natural-language to LTL executable semantic parser for grounded robotics. (2020). doi:https://doi.org/10.48550/arXiv.2008.03277

CBMM-Memo-122.pdf (1.03 MB)

Evangelopoulos, G., Voinea, S., Zhang, C., Rosasco, L. & Poggio, T. Learning An Invariant Speech Representation. (2014).

CBMM-Memo-022-1406.3884v1.pdf (1.81 MB)

Mhaskar, H., Liao, Q. & Poggio, T. Learning Functions: When Is Deep Better Than Shallow. (2016). at <https://arxiv.org/pdf/1603.00988v4.pdf>

Mlynarski, W. & McDermott, J. H. Learning Mid-Level Auditory Codes from Natural Sound Statistics. (2017).

MlynarskiMcDermott_Memo060.pdf (7.11 MB)

Poggio, T. & Cooper, Y. Loss landscape: SGD has a better view. (2020).

CBMM-Memo-107.pdf (1.03 MB)

Typos and small edits, ver11 (955.08 KB)

Small edits, corrected Hessian for spurious case (337.19 KB)

Harari, D., Gao, T., Kanwisher, N., Tenenbaum, J. B. & Ullman, S. Measuring and modeling the perception of natural and unconstrained gaze in humans and machines. (2016).

CBMM-Memo-059.pdf (1.71 MB)

Ross, C., Barbu, A. & Katz, B. Measuring Social Biases in Grounded Vision and Language Embeddings. (2021).

CBMM-Memo-126.pdf (1.32 MB)

Dubach, R., Abdallah, M. S. & Poggio, T. Multiplicative Regularization Generalizes Better Than Additive Regularization. (2025).

CBMM Memo 158.pdf (4.8 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)

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)

Conwell, C. et al. Neural Regression, Representational Similarity, Model Zoology Neural Taskonomy at Scale in Rodent Visual Cortex. (2021).

CBMM-Memo-131.pdf (9.37 MB)

Tan, C. & Poggio, T. Neural tuning size is a key factor underlying holistic face processing. (2014).

CBMM-Memo-021-1406.3793.pdf (387.79 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)

Miconi, T., Groomes, L. & Kreiman, G. A normalization model of visual search predicts single trial human fixations in an object search task. (2014).

CBMM-Memo-008.pdf (854.51 KB)

Galanti, T., Xu, M., Galanti, L. & Poggio, T. Norm-Based Generalization Bounds for Compositionally Sparse Neural Networks. (2023).

Norm-based bounds for convnets.pdf (1.2 MB)

Poggio, T., Rosasco, L., Shashua, A., Cohen, N. & Anselmi, F. Notes on Hierarchical Splines, DCLNs and i-theory. (2015).

CBMM Memo 037 (1.83 MB)

Liao, Q. & Poggio, T. Object-Oriented Deep Learning. (2017).

CBMM-Memo-070.pdf (963.54 KB)

Chen, X. & Yuille, A. Parsing Occluded People by Flexible Compositions. Computer Vision and Pattern Recognition (CVPR) (2015).

CBMM Memo 034.pdf (5.54 MB)

Lu, W., Lian, X. & Yuille, A. Parsing Semantic Parts of Cars Using Graphical Models and Segment Appearance Consistency. (2014).

CBMM-Memo-018_opt.pdf (5.02 MB)

Myanganbayar, B. et al. Partially Occluded Hands: A challenging new dataset for single-image hand pose estimation. (2018).

CBMM-Memo-097.pdf (8.53 MB)

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