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, Y., Muentener, P. & Schulz, L. The invisible hand: Toddlers connect probabilistic events with agentive causes. Cognitive Science 40, 23 (2016).

Wu_Muentener_Schulz_2016_InvisibleHand.pdf (307.21 KB)

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, Y., Muentener, P. & Schulz, L. One- to Four-year-olds’ Ability to Connect Diverse Positive Emotional Expressions to Their Probable Causes . Society for Research in Child Development (2017).

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)

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).

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

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. 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)

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

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

Wang, J. & Yuille, A. Semantic Part Segmentation using Compositional Model combing Shape and Appearance. CVPR (2015).

JianyuWangSemanticCVPR2015 (1).pdf (6.15 MB)

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

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

CBMM-Memo-082.pdf (869 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)

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, J. et al. Detecting Semantic Parts on Partially Occluded Objects. (2017).

CBMM-Memo-078.pdf (1.74 MB)

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