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

Conference Proceedings

Gerstenberg, T. & Tenenbaum, J. B. Understanding "almost": Empirical and computational studies of near misses. 38th Annual Meeting of the Cognitive Science Society (2016).

Understanding almost (Gerstenberg, Tenenbaum, 2016).pdf (4.08 MB)

Jing, L. et al. Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNN. 34th International Conference on Machine Learning 70, 1733-1741 (2017).

1612.05231.pdf (2.3 MB)

Han, Y., Poggio, T. & Cheung, B. System Identification of Neural Systems: If We Got It Right, Would We Know?. Proceedings of the 40th International Conference on Machine Learning, PMLR 202, 12430-12444 (2023).

han23d.pdf (797.48 KB)

Dapello, J. et al. Simulating a Primary Visual Cortex at the Front of CNNs Improves Robustness to Image Perturbations. Advances in Neural Information Processing Systems 33 pre-proceedings (NeurIPS 2020) (2020). at <https://proceedings.neurips.cc/paper/2020/hash/98b17f068d5d9b7668e19fb8ae470841-Abstract.html>

zhang, zhoutong et al. Shape and Material from Sound. Advances in Neural Information Processing Systems 30 1278–1288 (2017). at <http://papers.nips.cc/paper/6727-shape-and-material-from-sound.pdf>

Ren, Z., Wang, C. & Yuille, A. Scene-Domain Active Part Models for Object Representation. IEEE International Conference on Computer Vision (ICCV) 2497 - 2505 (2015). doi:10.1109/ICCV.2015.287

Ren_ICCV15.pdf (3.37 MB)

Gerstenberg, T., Halpern, J. Y. & Tenenbaum, J. B. Responsibility judgments in voting scenarios. Annual Meeting of the Cognitive Science Society (CogSci) 788-793 (2015). at <https://mindmodeling.org/cogsci2015/papers/0143/index.html>

Gerstenberg_paper0143.pdf (651.82 KB)

Houlihan, S. Dae, Ong, D., Cusimano, M. & Saxe, R. Reasoning about the antecedents of emotions: Bayesian causal inference over an intuitive theory of mind. Proceedings of the Annual Conference of the Cognitive Science Society 44, 854-861 (2022).

Houlihan 2022 Proceedings of the 44th Annual Conference of the Cognitive Science Society.pdf (687.98 KB)

Magid, R. & Schulz, L. Quit while you’re ahead: Preschoolers’ persistence and willingness to accept challenges are affected by social comparison. Annual Meeting of the Cognitive Science Society (CogSci) (2015).

15_Cogsci_Magid&Schulz.pdf (513.72 KB)

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)

Barbu, A. et al. ObjectNet: A large-scale bias-controlled dataset for pushing the limits of object recognition models. Neural Information Processing Systems (NeurIPS 2019) (2019).

9142-objectnet-a-large-scale-bias-controlled-dataset-for-pushing-the-limits-of-object-recognition-models.pdf (16.31 MB)

Bramley, N., Gerstenberg, T. & Tenenbaum, J. B. Natural science: Active learning in dynamic physical microworlds. 38th Annual Meeting of the Cognitive Science Society (2016).

Natural Science (Bramley, Gerstenberg, Tenenbaum, 2016).pdf (5.39 MB)

Krafft, P., Baker, C., Pentland, A. & Tenenbaum, J. B. Modeling Human Ad Hoc Coordination. AAAI (2016).

krafft_aaai2016.pdf (247.58 KB)

Smith, K. A. et al. Modeling Expectation Violation in Intuitive Physics with Coarse Probabilistic Object Representations. 33rd Conference on Neural Information Processing Systems (NeurIPS 2019) (2019). at <http: //physadept.csail.mit.edu/>

ADEPT_NeurIPS.pdf (11.07 MB)

Ben-Yosef, G., Assif, L., Harari, D. & Ullman, S. A model for full local image interpretation. Cognitive Science Society (2015).

Full object interpretation CogSci 2015 Print version.pdf (707.34 KB)

Feather, J., Durango, A., Gonzalez, R. & McDermott, J. H. Metamers of neural networks reveal divergence from human perceptual systems. NIPS 2019 (2019). at <https://papers.nips.cc/paper/9198-metamers-of-neural-networks-reveal-divergence-from-human-perceptual-systems>

Feather_etal_2019_NeurIPS_metamers.pdf (4.7 MB)

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)

Dasgupta, I., Bernstein, J., Rolnick, D. & Sompolinsky, H. Markov transitions between attractor states in a recurrent neural network. AAAI (2017).

aaai-abstract (1).pdf (357.72 KB)

Stephan, S., Willemsen, P. & Gerstenberg, T. Marbles in inaction: Counterfactual simulation and causation by omission. Proceedings of the 39th Annual Conference of the Cognitive Science Society (2017).

Marbles in Inaction Counterfactual Simulation and Causation by Omission, Stephan, Willemsen, Gerstenberg, 2017.pdf (1.46 MB)

Tang, H. et al. A machine learning approach to predict episodic memory formation. 2016 Annual Conference on Information Science and Systems (CISS) 539 - 544 (2016). doi:10.1109/CISS.2016.7460560

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).

Owens, A., Isola, P., McDermott, J. H., Freeman, W. T. & Torralba, A. Lecture Notes in Computer ScienceComputer Vision – ECCV 2016Ambient Sound Provides Supervision for Visual Learning. 14th European Conference on Computer Vision 801 - 816 (2016). doi:10.1007/978-3-319-46448-010.1007/978-3-319-46448-0_48

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)

Eric, W., Kevin, W. & Kreiman, G. Learning scene gist with convolutional neural networks to improve object recognition. 2018 52nd Annual Conference on Information Sciences and Systems (CISS) (2018). doi:10.1109/CISS.2018.8362305

08362305.pdf (3.17 MB)

Pagliana, N. & Rosasco, L. Implicit Regularization of Accelerated Methods in Hilbert Spaces. Neural Information Processing Systems (NeurIPS 2019) (2019).

9591-implicit-regularization-of-accelerated-methods-in-hilbert-spaces.pdf (451.14 KB)

Pages