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See, feel, act: Hierarchical learning for complex manipulation skills with multisensory fusion. Science Robotics 4, eaav3123 (2019).
Theoretical Issues in Deep Networks. (2019). CBMM Memo 100 v1 (1.71 MB) CBMM Memo 100 v3 (8/25/2019) (1.31 MB) CBMM Memo 100 v4 (11/19/2019) (1008.23 KB)
Theories of Deep Learning: Approximation, Optimization and Generalization . TECHCON 2019 (2019).
To find better neural network models of human vision, find better neural network models of primate vision. BioRxiv (2019). at <https://www.biorxiv.org/content/10.1101/688390v1.full>
Universal and Non-universal Features of Musical Pitch Perception Revealed by Singing. Current Biology (2019). doi:10.1016/j.cub.2019.08.020
Untangling in Invariant Speech Recognition. Neural Information Processing Systems (NeurIPS 2019) (2019). 9583-untangling-in-invariant-speech-recognition.pdf (2.09 MB)
A Virtual Reality Experimental Approach for Studying How the Brain Implements Attentive Behaviors. Tri-Institute 2019 Gateways to the Laboratory Summer Program (2019).
Visual Concept-Metaconcept Learning. Neural Information Processing Systems (NeurIPS 2019) (2019). 8745-visual-concept-metaconcept-learning.pdf (1.92 MB)
Visual Features for Invariant Coding by Face Selective Neurons . 2019 Conference on Cognitive Computational Neuroscience (CCN) (2019).
Psychology of Learning and Motivation 70, (2019).
Write, Execute, Assess: Program Synthesis with a REPL. Neural Information Processing Systems (NeurIPS 2019) (2019). 9116-write-execute-assess-program-synthesis-with-a-repl.pdf (3.9 MB)
Adaptive Coding for Dynamic Sensory Inference. eLife (2018).
An analysis of training and generalization errors in shallow and deep networks. (2018). CBMM-Memo-076.pdf (772.61 KB) CBMM-Memo-076v2.pdf (2.67 MB)
Assessing Language Proficiency from Eye Movements in Reading. 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2018). at <http://naacl2018.org/> 1804.07329.pdf (350.43 KB)
At 4.5 but not 5.5 years, children favor kin when the stakes are moderately high. PLOS ONE 13, (2018).
Biologically-plausible learning algorithms can scale to large datasets. (2018). CBMM-Memo-092.pdf (1.31 MB)
Brain-Observatory-Toolbox. (2018).
Brain-Score: Which Artificial Neural Network for Object Recognition is most Brain-Like?. bioRxiv preprint (2018). doi:10.1101/407007 Brain-Score bioRxiv.pdf (789.83 KB)
Can Deep Neural Networks Do Image Segmentation by Understanding Insideness?. (2018). CBMM-Memo-095.pdf (1.96 MB)
Classical generalization bounds are surprisingly tight for Deep Networks. (2018). CBMM-Memo-091.pdf (1.43 MB) CBMM-Memo-091-v2.pdf (1.88 MB)
Comparing human and monkey neural circuits for processing social scenes. Organization for Computational Neurosciences - CNS 2018 (2018). at <http://www.cnsorg.org/cns-2018>
Comparing human and monkey neural circuits for processing social scenes. Social & Affective Neuroscience Society (SANS) (2018). at <http://www.socialaffectiveneuro.org/conferences.html>