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.

Videos
Support Us

Publication

Search

Show only items where

Author

Type

Term

Year

Keyword

Found 912 results

Author Title [ Type

] Year

CBMM Memos

Nickel, M., Murphy, K., Tresp, V. & Gabrilovich, E. A Review of Relational Machine Learning for Knowledge Graphs: From Multi-Relational Link Prediction to Automated Knowledge Graph Construction. (2015).

CBMM Memo No. 028 (878.56 KB)

Anselmi, F. & Poggio, T. Representation Learning in Sensory Cortex: a theory. (2014).

CBMM-Memo-026_neuron_ver45.pdf (1.35 MB)

Liu, C. et al. Recurrent Multimodal Interaction for Referring Image Segmentation. (2018).

CBMM-Memo-079.pdf (10.16 MB)

Berzak, Y., Reichart, R. & Katz, B. Reconstructing Native Language Typology from Foreign Language Usage. (2014).

CBMM-Memo-007.pdf (683.75 KB)

Schulz, E., Tenenbaum, J. B., Duvenaud, D., Speekenbrink, M. & Gershman, S. J. Probing the compositionality of intuitive functions. (2016).

CBMM-Memo-048.pdf (815.72 KB)

Vaziri-Pashkam, M. Predicting actions before they occur. (2015).

PredictingActions (1.43 MB)

Supplemental Video 1: Experimental set up and task (16.38 MB)

Supplemental Video 2: An example FullVid and CutVid trial clips from experiment 4 (5.47 MB)

Gan, Y., Galanti, T., Poggio, T. & Malach, E. On the Power of Decision Trees in Auto-Regressive Language Modeling. (2024).

CBMM-Memo-149.pdf (2.11 MB)

Danhofer, D. A., D’Ascenzo, D., Dubach, R. & Poggio, T. Position: A Theory of Deep Learning Must Include Compositional Sparsity. (2025).

CBMM Memo 159.pdf (676.35 KB)

Netanyahu, A., Shu, T., Katz, B., Barbu, A. & Tenenbaum, J. B. PHASE: PHysically-grounded Abstract Social Events for Machine Social Perception. (2021).

CBMM-Memo-123.pdf (3.08 MB)

Poggio, T. A Perspective: Sparse Compositionality and Efficiently Computable Intelligence. (2026).

Perspective_SPCOMP-9.pdf (170.23 KB)

Gupte, A., Banburski, A. & Poggio, T. PCA as a defense against some adversaries. (2022).

CBMM-Memo-135.pdf (2.58 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)

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)

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

CBMM Memo 034.pdf (5.54 MB)

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

CBMM-Memo-070.pdf (963.54 KB)

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)

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)

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)

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)

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)

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)

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)

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)

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

CBMM Memo 158.pdf (4.8 MB)

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

CBMM-Memo-126.pdf (1.32 MB)

Pages