Publication
Export 897 results:
Theory II: Landscape of the Empirical Risk in Deep Learning. (2017).
CBMM Memo 066_1703.09833v2.pdf (5.56 MB)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
Theory of Deep Learning IIb: Optimization Properties of SGD. (2017).
CBMM-Memo-072.pdf (3.66 MB)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
Theory of Deep Learning III: explaining the non-overfitting puzzle. (2017).
CBMM-Memo-073.pdf (2.65 MB)
CBMM Memo 073 v2 (revised 1/15/2018) (2.81 MB)
CBMM Memo 073 v3 (revised 1/30/2018) (2.72 MB)
CBMM Memo 073 v4 (revised 12/30/2018) (575.72 KB)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
Theory of Intelligence with Forgetting: Mathematical Theorems Explaining Human Universal Forgetting using “Forgetting Neural Networks”. (2017).
CBMM-Memo-071.pdf (2.54 MB)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
Thinking fast or slow? A reinforcement-learning approach. Society for Personality and Social Psychology (2017).
KoolEtAl_SPSP_2017.pdf (670.35 KB)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
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)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
Two areas for familiar face recognition in the primate brain. Science 357, 591 - 595 (2017).
591.full_.pdf (928.29 KB)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
View-Tolerant Face Recognition and Hebbian Learning Imply Mirror-Symmetric Neural Tuning to Head Orientation. Current Biology 27, 1-6 (2017).
What is changing when: Decoding visual information in movies from human intracranial recordings. Neuroimage (2017). doi:https://doi.org/10.1016/j.neuroimage.2017.08.027
When and Why Are Deep Networks Better Than Shallow Ones?. AAAI-17: Thirty-First AAAI Conference on Artificial Intelligence (2017).
Why and when can deep-but not shallow-networks avoid the curse of dimensionality: A review. International Journal of Automation and Computing 1-17 (2017). doi:10.1007/s11633-017-1054-2
art%3A10.1007%2Fs11633-017-1054-2.pdf (1.68 MB)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
Why does deep and cheap learning work so well?. Journal of Statistical Physics 168, 1223–1247 (2017).
1608.08225.pdf (2.14 MB)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
Anchoring and Agreement in Syntactic Annotations. (2016).
CBMM-Memo-055.pdf (768.54 KB)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
Atoms of recognition in human and computer vision. PNAS 113, 2744–2749 (2016).
mirc_author_manuscript_with_figures_and_SI-2.pdf (1.65 MB)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
A Bayesian nonparametric approach for uncovering rat hippocampal population codes during spatial navigation. Journal of Neuroscience Methods 263, (2016).
Journal of Neuroscience Methods (2.27 MB)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
Bayesian nonparametric methods for discovering latent structures of rat hippocampal ensemble spikes. IEEE Workshop on Machine Learning for Signal Processing (2016).
MLSP16 (1).pdf (1.04 MB)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
Bottom-up and Top-down Input Augment the Variability of Cortical Neurons. Neuron 91(3), 540-547 (2016).
Bridging the Gaps Between Residual Learning, Recurrent Neural Networks and Visual Cortex. (2016).
CBMM Memo No. 047 (1.29 MB)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
Building machines that learn and think like people. (2016).
machines_that_think.pdf (3.45 MB)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
Cascade of neural processing orchestrates cognitive control in human frontal cortex [code]. (2016). at <http://klab.tch.harvard.edu/resources/tangetal_stroop_2016.html>
Cascade of neural processing orchestrates cognitive control in human frontal cortex [dataset]. (2016). at <http://klab.tch.harvard.edu/resources/tangetal_stroop_2016.html>
Cascade of neural processing orchestrates cognitive control in human frontal cortex. eLIFE (2016). doi:10.7554/eLife.12352
Manuscript (1.83 MB)
![application/pdf PDF icon](/modules/file/icons/application-pdf.png)
Children’s Expectations and Understanding of Kinship as a Social Category. Frontiers in Psychology 7, 1664-1078 (2016).
Scientists Making a Difference: One Hundred Eminent Behavioral and Brain Scientists Talk about Their Most Important Contributions (Cambridge University Press, 2016).