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Found 904 results
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Mao, J. et al. Generation and Comprehension of Unambiguous Object Descriptions. The Conference on Computer Vision and Pattern Recognition (CVPR) (2016). at <https://github.com/ mjhucla/Google_Refexp_toolbox>PDF icon object_description_cbmm.pdf (2.21 MB)
Mao, J. et al. Learning like a Child: Fast Novel Visual Concept Learning from Sentence Descriptions of Images. International Conference of Computer Vision (2015). at <www.stat.ucla.edu/~junhua.mao/projects/child_learning.html>PDF icon child_learning_iccv2015.pdf (1.16 MB)
Mao, J. et al. Deep Captioning with Multimodal Recurrent Neural Networks (m-RNN). (2015).PDF icon CBMM Memo 033.pdf (839.42 KB)
Mao, J., Xu, J., Jing, Y. & Yuille, A. Training and Evaluating Multimodal Word Embeddings with Large-scale Web Annotated Images. NIPS 2016 (2016).PDF icon 6590-training-and-evaluating-multimodal-word-embeddings-with-large-scale-web-annotated-images.pdf (1.57 MB)
Marciniak, K., Dicke, P. W. & Thier, P. Monkeys head-gaze following is fast, precise and not fully suppressible. Proc Biol Sci 282, 20151020 (2015).PDF icon Marciniak et al 2015 Proc R Soc B Monkeys head gaze following is fast precise and not fully suppressible.pdf (7.07 MB)
Marques, T., Schrimpf, M. & DiCarlo, J. J. Multi-scale hierarchical neural network models that bridge from single neurons in the primate primary visual cortex to object recognition behavior. bioRxiv (2021).PDF icon 2021.03.01.433495v2.full_.pdf (3.23 MB)
Marques, T., Schrimpf, M. & DiCarlo, J. J. Hierarchical neural network models that more closely match primary visual cortex tend to better explain higher level visual cortical responses . COSYNE (2020).
Marques, T. & DiCarlo, J. J. A meta-analysis of ANNs as models of primate V1 . Bernstein (2019).
McCoy, J. P. & Ullman, T. Judgments of effort for magical violations of intuitive physics. PLOS ONE 14, e0217513 (2019).
McCoy, J. P. & Ullman, T. D. A Minimal Turing Test. Journal of Experimental Social Psychology 79, 1 - 8 (2018).
McNamee, D., Stachenfeld, K., Botvinick, M. M. & Gershman, S. J. Flexible modulation of sequence generation in the entorhinal-hippocampal system. Nature Neuroscience (2021). doi:10.1038/s41593-021-00831-7
McPherson, M. J., Grace, R. C. & McDermott, J. H. Harmonicity aids hearing in noise. Attention, Perception, & Psychophysics (2022). doi:10.3758/s13414-021-02376-0
McPherson, M. J. & McDermott, J. H. Time-dependent discrimination advantages for harmonic sounds suggest efficient coding for memory. Proceedings of the National Academy of Sciences 117, 32169 - 32180 (2020).
McWalter, R. & McDermott, J. H. Illusory sound texture reveals multi-second statistical completion in auditory scene analysis. Nature Communications 10, (2019).
Meanti*, G. et al. Estimating Koopman operators with sketching to provably learn large scale dynamical systems. 37th Conference on Neural Information Processing Systems (NeurIPS 2023) (2023). at <https://proceedings.neurips.cc/paper_files/paper/2023/file/f3d1e34a15c0af0954ae36a7f811c754-Paper-Conference.pdf>
Melloni, L. et al. An adversarial collaboration protocol for testing contrasting predictions of global neuronal workspace and integrated information theory. PLOS ONE 18, e0268577 (2023).PDF icon journal.pone_.0268577.pdf (1.99 MB)
Mendoza-Halliday, D. & Martinez-Trujillo, J. Neuronal population coding of perceived and memorized visual features in the lateral prefrontal cortex. Nature Communications 8, (2017).
Mendoza-Halliday, D., Schneiderman, M., Kaul, C. & Martinez-Trujillo, J. Combined effects of feature-based working memory and feature-based attention on the perception of visual motion direction. Journal of Vision 11, (2011).
Mendoza-Halliday, D. et al. A ubiquitous spectrolaminar motif of local field potential power across the primate cortexAbstract. Nature Neuroscience 27, 547 - 560 (2024).
Mendoza-Halliday, D., Schneiderman, M., Kaul, C. & Martinez-Trujillo, J. Combined effects of feature-based working memory and feature-based attention on the perception of visual motion direction. Journal of Vision 11, (2011).
Mendoza-Halliday, D., Xu, H., Azevedo, F. A. C. & Desimone, R. Dissociable neuronal substrates of visual feature attention and working memory. Neuron 112, 850 - 863.e6 (2024).
Mendoza-Halliday, D., Torres, S. & Martinez-Trujillo, J. Mechanisms of Sensory Working Memory: Attention and Performance XXV. (Elsevier Inc. , 2015). at <https://www.sciencedirect.com/book/9780128013717/mechanisms-of-sensory-working-memory>
Mendoza-Halliday, D., Torres, S. & Martinez-Trujillo, J. Sharp emergence of feature-selective sustained activity along the dorsal visual pathway. Nature Neuroscience 7, (2014).
Meyers, E. Review of the CBMM workshop on the Turing++ Question: 'who is there?'. (2016).PDF icon Review of the CBMM workshop on the Turing++ Question- 'who is there?' .pdf (555.71 KB)
Meyers, E. Dynamic population coding and its relationship to working memory. Journal of Neurophysiology 120, 2260 - 2268 (2018).

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