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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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Yaari, A. Uri et al. Multi-resolution modeling of a discrete stochastic process identifies causes of cancer. International Conference on Learning Representations (2021). at <https://openreview.net/forum?id=KtH8W3S_RE>

Yaari, A. et al. The Aligned Multimodal Movie Treebank: An audio, video, dependency-parse treebank. Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (2022).

Yamada, M., D'Amario, V., Takemoto, K., Boix, X. & Sasaki, T. Transformer Module Networks for Systematic Generalization in Visual Question Answering. (2022).

CBMM-Memo-121.pdf (1.06 MB)

version 2 (3/22/2023) (1.33 MB)

Yan, P., Magid, R. & Schulz, L. Preschoolers expect others to learn rationally from evidence. Annual Conference of the Cognitive Science Society (2014).

Yan, Magid, & Schulz_CogSci14_REVISED.pdf (302.4 KB)

Yang, C. et al. Evolutionary and biomedical insights from a marmoset diploid genome assembly. Nature (2021). doi:10.1038/s41586-021-03535-x

Yang, Z. & Freiwald, W. A. Joint encoding of facial identity, orientation, gaze, and expression in the middle dorsal face areaSignificance. Proceedings of the National Academy of Sciences 118, (2021).

Yang, S., Bill, J., Drugowitsch, J. & Gershman, S. J. Human visual motion perception shows hallmarks of Bayesian structural inference. Scientific Reports 11, (2021).

Yildirim, I., Wu, J., Kanwisher, N. & Tenenbaum, J. B. An integrative computational architecture for object-driven cortex. Current Opinion in Neurobiology 55, 73 - 81 (2019).

Yildirim, I., Siegel, M. & Tenenbaum, J. B. Perceiving Fully Occluded Objects with Physical Simulation. Cognitive Science Conference (CogSci) (2015).

Yildirim, I., Freiwald, W. A. & J., T. Efficient inverse graphics in biological face processing. bioRxiv (2018). at <https://www.biorxiv.org/content/early/2018/04/02/282798>

Yildirim, I., Kulkarni, T., Freiwald, W. A. & Tenenbaum, J. B. Efficient and robust analysis-by-synthesis in vision: A computational framework, behavioral tests, and modeling neuronal representations. Annual Conference of the Cognitive Science Society (2015).

yildirimetal_cogsci15.pdf (3.22 MB)

Yildirim, I., Belledonne, M., Freiwald, W. A. & Tenenbaum, J. B. Efficient inverse graphics in biological face processing. Science Advances 6, eaax5979 (2020).

eaax5979.full_.pdf (3.22 MB)

Yildirim, I. et al. Causal and compositional generative models in online perception. 39th Annual Meeting of the Cognitive Science Society - COGSCI 2017 (2017). at <https://mindmodeling.org/cogsci2017/papers/0266/index.html>

Yildirim, I., Kulkarni, T., Freiwald, W. A. & Tenenbaum, J. B. Explaining Monkey Face Patch System as Efficient Analysis-by-Synthesis. (2014).

yildirimetal_cosyne15.pdf (313.57 KB)

Yildirim, I., Siegel, M. H., Soltani, A. A., Chaudhuri, S. Ray & Tenenbaum, J. B. Perception of 3D shape integrates intuitive physics and analysis-by-synthesis. Nature Human Behaviour (2023). doi:10.1038/s41562-023-01759-7

Yildirim, I., Gerstenberg, T., Saeed, B., Toussant, M. & Tenenbaum, J. B. Physical problem solving: Joint planning with symbolic, geometric, and dynamic constraints. Proceedings of the 39th Annual Conference of the Cognitive Science Society (2017).

Physical problem solving Joint planning with symbolic, geometric, and dynamic constraints, Yildirim et al., 2017.pdf (2.46 MB)

Yildirim, I. & Janner, M. Causal and compositional generative models in online perception. 39th Annual Conference of the Cognitive Science Society (Belledonne, M., Wallraven, C., Freiwald, W. A. & Tenenbaum, J. B.) (2017).

yildirim_janner_2_1.pdf (6.88 MB)

Yu, H., Siddharth, N., Barbu, A. & Siskind, J. Mark. A Compositional Framework for Grounding Language Inference, Generation, and Acquisition in Video. (2015). doi:doi:10.1613/jair.4556

Yu, C., Burgess, N., Sahani, M. & Gershman, S. J. Successor-Predecessor Intrinsic Exploration. Advances in Neural Information Processing Systems 36 (NeurIPS 2023) (2023). at <https://proceedings.neurips.cc/paper_files/paper/2023/hash/e6f2b968c4ee8ba260cd7077e39590dd-Abstract-Conference.html>

Yuille, A. & Liu, C. Deep Nets: What have they ever done for Vision?. (2018).

CBMM-Memo-088.pdf (7.88 MB)

Yuille, A. & Mottaghi, R. Complexity of Representation and Inference in Compositional Models with Part Sharing. (2015).

CBMM Memo 031.pdf (1.14 MB)

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Zador, A. et al. Catalyzing next-generation Artificial Intelligence through NeuroAIAbstract. Nature Communications 14, (2023).

Zarco, W. & Freiwald, W. A. Visual Features for Invariant Coding by Face Selective Neurons . 2019 Conference on Cognitive Computational Neuroscience (CCN) (2019).

Zaslavsky, N., Hu, J. & Levy, R. Emergence of Pragmatic Reasoning From Least-Effort Optimization . 13th International Conference on the Evolution of Language (EvoLang) (2020).

Zaslavsky, N., Maldonado, M. & Culbertson, J. Let's talk (efficiently) about us: Person systems achieve near-optimal compression. Proceedings of the Annual Meeting of the Cognitive Science Society 43, (2021).

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