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Found 904 results
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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).PDF icon 9142-objectnet-a-large-scale-bias-controlled-dataset-for-pushing-the-limits-of-object-recognition-models.pdf (16.31 MB)
Bardon, A., Xiao, W., Ponce, C. R., Livingstone, M. S. & Kreiman, G. Face neurons encode nonsemantic features. Proceedings of the National Academy of Sciences 119, (2022).
Bashivan, P., Kar, K. & DiCarlo, J. J. Neural Population Control via Deep Image Synthesis. Science 364, (2019).PDF icon Author's last draft (18.45 MB)
Bass, I., Smith, K. A., Bonawitz, E. & Ullman, T. Partial Mental Simulation Explains Fallacies in Physical Reasoning. psyArXiv (2021). at <https://psyarxiv.com/y4a8x>
Becker, L. A. et al. Eszopiclone and Zolpidem Produce Opposite Effects on Hippocampal Ripple DensityDataSheet1.docx. Frontiers in Pharmacology 12, (2022).
Becker, L. A., Penagos, H., Manoach, D. S., Wilson, M. A. & Varela, C. Disruption of CA1 Sharp-Wave Ripples by the nonbenzodiazepine hypnotic eszopiclone . Society for Neuroscience (2019).
Belbute-Peres, Fde Avila, Smith, K. A., Allen, K., Tenenbaum, J. B. & Kolter, Z. End-to-end differentiable physics for learning and control. Advances in Neural Information Processing Systems 31 (NIPS 2018) (2018).PDF icon 7948-end-to-end-differentiable-physics-for-learning-and-control.pdf (794.17 KB)
Ben-Yosef, G., Kreiman, G. & Ullman, S. What can human minimal videos tell us about dynamic recognition models?. International Conference on Learning Representations (ICLR 2020) (2020). at <https://baicsworkshop.github.io/pdf/BAICS_1.pdf>PDF icon Authors' final version (516.09 KB)
Ben-Yosef, G., Yachin, A. & Ullman, S. A model for interpreting social interactions in local image regions. AAAI Spring Symposium Series, Science of Intelligence (2017). at <http://www.aaai.org/ocs/index.php/SSS/SSS17/paper/view/15354>PDF icon 2017-Ben-Yosef_Yachin_Ullman-A_model_for_interpreting_social_interactions_in_local_image_regions.pdf (1.53 MB)
Ben-Yosef, G. & Ullman, S. Image interpretation above and below the object level. Proceedings of the Royal Society: Interface Focus (2018).PDF icon 2018-BenYosef_Ullman-Image_interpretation_above_and_below the object_level.pdf (3.26 MB)
Ben-Yosef, G., Assif, L., Harari, D. & Ullman, S. A model for full local image interpretation. Cognitive Science Society (2015).PDF icon Full object interpretation CogSci 2015 Print version.pdf (707.34 KB)
Ben-Yosef, G., Assif, L. & Ullman, S. Full interpretation of minimal images. (2017).PDF icon CBMM Memo 061 v.1 (4.64 MB)PDF icon CBMM Memo 061 v.2 (5.41 MB)
Ben-Yosef, G., Assif, L. & Ullman, S. Full interpretation of minimal images. Cognition 171, 65 - 84 (2018).
Ben-Yosef, G., Assif, L. & Ullman, S. Full interpretation of minimal images. Cognition 171, 65-84 (2018).PDF icon Full interpretation of minimal images.pdf (4.55 MB)
Ben-Yosef, G., Yachin, A. & Ullman, S. Recognizing and Interpreting Social Interactions in Local Image Regions. The 24th Annual Workshop on Object Perception, Attention, and Memory (OPAM), Boston, MA (2016).
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 CBMM-Memo-094-dynamic-figures.zip (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)
Ben-Yosef, G., Kreiman, G. & Ullman, S. Minimal videos: Trade-off between spatial and temporal information in human and machine vision. Cognition (2020). doi:10.1016/j.cognition.2020.104263
Ben-Yosef, G. & Ullman, S. Image interpretation above and below the object level. (2018).PDF icon CBMM-Memo-089.pdf (2.06 MB)
Ben-Yosef, G. & Ullman, S. Image interpretation above and below the object level. Interface Focus 8, 20180020 (2018).
Quality Early Learning: Nurturing Children's Potential. (The World Bank, 2022). doi:10.1596/978-1-4648-1795-3
Bergen, L., Levy, R. & Goodman, N. D. Pragmatic Reasoning through Semantic Inference. Semantics and Pragmatics Vol 9 (2016) , (2016).PDF icon BergenLevyGoodman2015.pdf (1.12 MB)
Bergen, L. & Goodman, N. D. The strategic use of noise in pragmatic reasoning. (2014).
Berrios, W. & Deza, A. Joint rotational invariance and adversarial training of a dual-stream Transformer yields state of the art Brain-Score for Area V4. BrainScore Workshop at COSYNE (2022). at <https://openreview.net/pdf?id=SOulrWP-Xb5>
Berzak, Y., Barbu, A., Harari, D., Katz, B. & Ullman, S. Do You See What I Mean? Visual Resolution of Linguistic Ambiguities. Conference on Empirical Methods in Natural Language Processing, Lisbon, Portugal. (2015).
Berzak, Y., Reichart, R. & Katz, B. Contrastive Analysis with Predictive Power: Typology Driven Estimation of Grammatical Error Distributions in ESL. (2016).PDF icon memo-50.pdf (493.74 KB)

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