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Myanganbayar, B. et al. Partially Occluded Hands: A challenging new dataset for single-image hand pose estimation. (2018).PDF icon CBMM-Memo-097.pdf (8.53 MB)
Kool, W., Gershman, S. J. & Cushman, F. A. Planning Complexity Registers as a Cost in Metacontrol. Journal of Cognitive Neuroscience 30, 1391 - 1404 (2018).
Wu, Y., Baker, C., Tenenbaum, J. B. & Schulz, L. Rational inference of beliefs and desires from emotional expressions. Cognitive Science 42, (2018).PDF icon 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).
Tang, H. et al. Recurrent computations for visual pattern completion. Proceedings of the National Academy of Sciences (2018). doi:10.1073/pnas.1719397115PDF icon 1719397115.full_.pdf (1.1 MB)
Liu, C. et al. Recurrent Multimodal Interaction for Referring Image Segmentation. (2018).PDF icon CBMM-Memo-079.pdf (10.16 MB)
Hamrick, J. B. et al. Relational inductive bias for physical construction in humans and machines. In Proceedings of the Annual Meeting of the Cognitive Science Society (CogSci 2018) (2018).PDF icon 1806.01203.pdf (1022.51 KB)
Wang, Y. - S., Liu, C., Zeng, X. & Yuille, A. Scene Graph Parsing as Dependency Parsing. (2018).PDF icon CBMM-Memo-082.pdf (869 KB)
Owaki, T. et al. Searching for visual features that explain response variance of face neurons in inferior temporal cortex. PLOS ONE 13, e0201192 (2018).
Adhya, D. et al. Shared gene co-expression networks in autism from induced pluripotent stem cell (iPSC) neurons. BioRxiv (2018). doi:10.1101/349415
Arend, L. et al. Single units in a deep neural network functionally correspond with neurons in the brain: preliminary results. (2018).PDF icon CBMM-Memo-093.pdf (2.99 MB)
Zhang, Z. et al. Single-Shot Object Detection with Enriched Semantics. Conference on Computer Vision and Pattern Recognition (CVPR) (2018). at <>
Zhang, Z. et al. Single-Shot Object Detection with Enriched Semantics. (2018).PDF icon CBMM-Memo-084.pdf (1.92 MB)
Ben-Yosef, G., Kreiman, G. & Ullman, S. Spatiotemporal interpretation features in the recognition of dynamic images. (2018).PDF icon CBMM-Memo-094.pdf (1.21 MB)Package icon (1.8 MB)File fig1.ppsx (147.67 KB)File fig2.ppsx (419.72 KB)File fig4.ppsx (673.41 KB)File figS1.ppsx (587.88 KB)File figS2.ppsx (281.56 KB)
Hart, Y. et al. The statistical shape of geometric reasoning. Scientific Reports 8, (2018).
Lewis, O. Structured learning and inference with neural networks and generative models. (2018).
Kell, A. J. E., Yamins, D. L. K., Shook, E. N., Norman-Haignere, S. V. & McDermott, J. H. A task-optimized neural network replicates human auditory behavior, predicts brain responses, and reveals a cortical processing hierarchy. Neuron 98, (2018).
Poggio, T. & Liao, Q. Theory I: Deep networks and the curse of dimensionality. Bulletin of the Polish Academy of Sciences: Technical Sciences 66, (2018).PDF icon 02_761-774_00966_Bpast.No_.66-6_28.12.18_K1.pdf (1.18 MB)
Poggio, T. & Liao, Q. Theory II: Deep learning and optimization. Bulletin of the Polish Academy of Sciences: Technical Sciences 66, (2018).PDF icon 03_775-788_00920_Bpast.No_.66-6_31.12.18_K2.pdf (5.43 MB)
Banburski, A. et al. Theory III: Dynamics and Generalization in Deep Networks. (2018).PDF icon Original, intermediate versions are available under request (2.67 MB)PDF icon CBMM Memo 90 v12.pdf (4.74 MB)PDF icon Theory_III_ver44.pdf Update Hessian (4.12 MB)PDF icon Theory_III_ver48 (Updated discussion of convergence to max margin) (2.56 MB)PDF icon fixing errors and sharpening some proofs (2.45 MB)
Powell, L. J. & Spelke, E. S. Third-Party Preferences for Imitators in Preverbal Infants. Open Mind 2, 61 - 71 (2018).
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 <>PDF icon trading-robust-representations-for-sample-complexity-through-self-supervised-visual-experience.pdf (3.32 MB)PDF icon NeurIPS2018_Poster.pdf (6.12 MB)
Wang, J. et al. Visual concepts and compositional voting. (2018).PDF icon CBMM-Memo-087.pdf (3.37 MB)
Wang, J. et al. Visual Concepts and Compositional Voting. Annals of Mathematical Sciences and Applications (AMSA) 3, 151–188 (2018).
Zhang, M., Feng, J., Lim, J. Hwee, Zhao, Q. & Kreiman, G. What am I searching for?. (2018).PDF icon CBMM-Memo-096.pdf (1.74 MB)