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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Wu, J., Yildirim, I., Lim, J. J., Freeman, W. T. & Tenenbaum, J. B. Galileo: Perceiving physical object properties by integrating a physics engine with deep learning. NIPS 2015 (2015). at <https://papers.nips.cc/paper/5780-galileo-perceiving-physical-object-properties-by-integrating-a-physics-engine-with-deep-learning>

Wu, J. et al. MarrNet: 3D Shape Reconstruction via 2.5D Sketches. Advances in Neural Information Processing Systems 30 540–550 (2017). at <http://papers.nips.cc/paper/6657-marrnet-3d-shape-reconstruction-via-25d-sketches.pdf>

MarrNet: 3D Shape Reconstruction via 2.5D Sketches (6.25 MB)

Wu, K., Wu, E. & Kreiman, G. Learning Scene Gist with Convolutional Neural Networks to Improve Object Recognition. arXiv | Cornell University arXiv:1803.01967, (2018).

Wu, J., Lu, E., Kohli, P., Freeman, W. T. & Tenenbaum, J. B. Learning to See Physics via Visual De-animation. Advances in Neural Information Processing Systems 30 152–163 (2017). at <http://papers.nips.cc/paper/6620-learning-to-see-physics-via-visual-de-animation.pdf>

Learning to See Physics via Visual De-animation (1.11 MB)

Woo, B. M. & Spelke, E. S. Infants and toddlers leverage their understanding of action goals to evaluate agents who help others. Child Development (2023). doi:10.1111/cdev.13895

Woo, B. & Spelke, E. Eight-Month-Old Infants’ Social Evaluations of Agents Who Act on False Beliefs. Proceedings of the Annual Meeting of the Cognitive Science Society 44, (2022).

Woo, B. M. & Spelke, E. S. Toddlers’ social evaluations of agents who act on false beliefs. Developmental Science 26, (2022).

Wong, A. & Yuille, A. One Shot Learning via Compositions of Meaningful Patches. International Conference on Computer Vision (ICCV) (2015).

AlexWongOneShotCVPR2015.pdf (1.83 MB)

Wong, A. & Yuille, A. One Shot Learning by Composition of Meaningful Patches. International Conference on Computer Vision (ICCV) (2015).

AlexWongOneShotCVPR2015.pdf (1.83 MB)

Wirtshafter, H. S. & Wilson, M. A. Artificial intelligence insights into hippocampal processing. Frontiers in Computational Neuroscience 16, (2022).

Winston, P. Henry & Holmes, D. Character-building stories. Advances in Cognitive Systems (2017).

Winston, P. Henry. Model-based Story Summary. 6th Workshop on Computational Models of Narrative (2015). doi:10.4230/OASIcs.CMN.2015.157

Winston, P. Henry. Marvin L. Minsky (1927–2016) Scientist and inventor was a visionary founder of AI. (2016).

Marvin L. Minsky (1927–2016) Scientist and inventor was a visionary founder of AI.pdf (559.42 KB)

Winston, P. Henry. The Genesis Story Understanding and Story Telling System A 21st Century Step toward Artificial Intelligence. (2014).

CBMM-Memo-019_StoryWhitePaper.pdf (894.38 KB)

Weisholtz, D. S. et al. Localized task-invariant emotional valence encoding revealed by intracranial recordingsAbstract. Social Cognitive and Affective Neuroscience (2021). doi:10.1093/scan/nsab134

Wang, C., Wang, Y., Lin, Z., Yuille, A. & Gao, W. Robust Estimation of 3D Human Poses from a Single Image. (2014).

CBMM-Memo-013.pdf (510.23 KB)

Wang, C. et al. BrainBERT: Self-supervised representation learning for Intracranial Electrodes. International Conference on Learning Representations (2023). at <https://openreview.net/forum?id=xmcYx_reUn6>

985_brainbert_self_supervised_repr.pdf (9.71 MB)

Wang, P. & Yuille, A. DOC: Deep OCclusion Recovering From A Single Image. ECCV (2016).

Wang, J. et al. Detecting Semantic Parts on Partially Occluded Objects. British Machine Vision Conference (BMVC) (2017). at <https://bmvc2017.london/proceedings/>

Wang, J. et al. Visual concepts and compositional voting. (2018).

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).

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)

Wang, C., Ross, C., Kuo, Y. - L., Katz, B. & Barbu, A. Learning a Natural-language to LTL Executable Semantic Parser for Grounded Robotics. (Proceedings of Conference on Robot Learning (CoRL-2020), 2020). at <https://corlconf.github.io/paper_385/>

Wang, B. & Ponce, C. R. A Geometric Analysis of Deep Generative Image Models and Its Applications. Proc. International Conference on Learning Representations, 2021 (2021).

Wang, Y. - S., Liu, C., Zeng, X. & Yuille, A. Scene Graph Parsing as Dependency Parsing. (2018).

CBMM-Memo-082.pdf (869 KB)

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