Export 663 results:
Invariant representations for action recognition in the visual system. Computational and Systems Neuroscience (2015).
Invariant representations for action recognition in the visual system. Vision Sciences Society 15, (2015).
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>
Learning with a Wasserstein Loss. Advances in Neural Information Processing Systems (NIPS 2015) 28 (2015). at <http://arxiv.org/abs/1506.05439>
Learning with Group Invariant Features: A Kernel Perspective. NIPS 2015 (2015). at <https://papers.nips.cc/paper/5798-learning-with-group-invariant-features-a-kernel-perspective>
Learning with incremental iterative regularization. NIPS 2015 (2015). at <https://papers.nips.cc/paper/6015-learning-with-incremental-iterative-regularization>
Less is More: Nyström Computational Regularization. NIPS 2015 (2015). at <https://papers.nips.cc/paper/5936-less-is-more-nystrom-computational-regularization>
Lust and the Turing test [Nature] . (2015). at <http://blogs.nature.com/aviewfromthebridge/2015/05/27/lust-and-the-turing-test/>
Metareasoning in Symbolic Domains. NIPS Workshop | Bounded Optimality and Rational Metareasoning (2015). at <https://sites.google.com/site/boundedoptimalityworkshop/>
A model for full local image interpretation. Cognitive Science Society (2015).
Model-based Story Summary. 6th Workshop on Computational Models of Narrative (2015). doi:10.4230/OASIcs.CMN.2015.157.
Monkeys head-gaze following is fast, precise and not fully suppressible. Proc Biol Sci 282, 20151020 (2015).
Neural ensemble communities: open-source approaches to hardware for large-scale electrophysiology. Current Opinion in Neurobiology 32, 53 - 59 (2015).
Not So Innocent: Toddlers’ Inferences About Costs and Culpability. Psychological Science 26, 633-40 (2015).
One Shot Learning by Composition of Meaningful Patches. International Conference on Computer Vision (ICCV) (2015).
One Shot Learning via Compositions of Meaningful Patches. International Conference on Computer Vision (ICCV) (2015).
Optogenetic feedback control of neural activity. Elife 4, e07192 (2015).
Our Mother the Machine, by Dan Rockmore [Huffpost] . (2015). at <http://www.huffingtonpost.com/dan-rockmore/our-mother-the-machine_b_7273504.html>
Parsing Occluded People by Flexible Compositions. Computer Vision and Pattern Recognition (CVPR) (2015).
Parts-based representations of perceived face movements in the superior temporal sulcus. Society for Neuroscience Annual Meeting (2015). at <https://www.sfn.org/~/media/SfN/Documents/Annual%20Meeting/FinalProgram/NS2015/Daily%20Books%202015/AM15Monday.ashx>