All Publications

2019

CBMM Memo No.
102
T. Poggio, Kur, G., and Banburski, A., “Double descent in the condition number”. 2019.PDF icon Fixing typos, clarifying error in y, best approach is crossvalidation (837.18 KB)PDF icon Incorporated footnote in text plus other edits (854.05 KB)PDF icon Deleted previous discussion on kernel regression and deep nets: it will appear, extended, in a separate paper (795.28 KB)PDF icon correcting a bad typo (261.24 KB)PDF icon Deleted plot of condition number of kernel matrix: we cannot get a double descent curve  (769.32 KB)
CBMM Funded
Y. - L. Kuo, Katz, B., and Barbu, A., “Deep Compositional Robotic Planners that Follow Natural Language Commands.”, Workshop on Visually Grounded Interaction and Language (ViGIL) at the Thirty-third Annual Conference on Neural Information Processing Systems (NeurIPS). Vancouver Convention Centre, Vancouver, Canada, 2019.
CBMM Funded
W. Młynarski and McDermott, J. H., “Ecological origins of perceptual grouping principles in the auditory system”, Proceedings of the National Academy of Sciences, vol. 116, no. 50, pp. 25355 - 25364, 2019.
CBMM Funded
C. Ross, Berzak, Y., Katz, B., and Barbu, A., “Learning Language from Vision.”, in Workshop on Visually Grounded Interaction and Language (ViGIL) at the Thirty-third Annual Conference on Neural Information Processing Systems (NeurIPS), Vancouver Convention Center, Vancouver, Canada, 2019.
CBMM Funded
A. Barbu, Mayo, D., Alverio, J., Luo, W., Wang, C., Gutfreund, D., Tenenbaum, J. B., and Katz, B., “ObjectNet: A large-scale bias-controlled dataset for pushing the limits of object recognition models”, Neural Information Processing Systems (NeurIPS 2019). Vancouver, Canada, 2019.PDF icon 9142-objectnet-a-large-scale-bias-controlled-dataset-for-pushing-the-limits-of-object-recognition-models.pdf (16.31 MB)
CBMM Funded
K. Brewer, Mittman, B., Kominsky, J., and Henes, J., “Open Source Subject Database Project (OSSDP)”. Center for Brains, Minds and Machines, 2019.
CBMM Funded
K. Ellis, Nye, M., Pu, Y., Sosa, F., Tenenbaum, J. B., and Solar-Lezama, A., “Write, Execute, Assess: Program Synthesis with a REPL”, Neural Information Processing Systems (NeurIPS 2019). Vancouver, Canada, 2019.PDF icon 9116-write-execute-assess-program-synthesis-with-a-repl.pdf (3.9 MB)
CBMM Funded
J. Feather, Durango, A., Gonzalez, R., and McDermott, J. H., “Metamers of neural networks reveal divergence from human perceptual systems”, NIPS 2019. Vancouver, Canada, 2019.PDF icon Feather_etal_2019_NeurIPS_metamers.pdf (4.7 MB)
CBMM Funded
C. Han, Mao, J., Gan, C., Tenenbaum, J. B., and Wu, J., “Visual Concept-Metaconcept Learning”, Neural Information Processing Systems (NeurIPS 2019). Vancouver, Canada, 2019.PDF icon 8745-visual-concept-metaconcept-learning.pdf (1.92 MB)
CBMM Funded
R. McWalter and McDermott, J. H., “Illusory sound texture reveals multi-second statistical completion in auditory scene analysis”, Nature Communications, vol. 10, no. 1, 2019.
CBMM Related
N. Muecke, Neu, G., and Rosasco, L., “Beating SGD Saturation with Tail-Averaging and Minibatching”, Neural Information Processing Systems (NeurIPS 2019). Vancouver, Canada, 2019.PDF icon 9422-beating-sgd-saturation-with-tail-averaging-and-minibatching.pdf (389.35 KB)
CBMM Funded
N. Pagliana and Rosasco, L., “Implicit Regularization of Accelerated Methods in Hilbert Spaces”, Neural Information Processing Systems (NeurIPS 2019). Vancouver, Canada, 2019.PDF icon 9591-implicit-regularization-of-accelerated-methods-in-hilbert-spaces.pdf (451.14 KB)
CBMM Funded
K. A. Smith, Mei, L., Yao, S., Wu, J., Spelke, E. S., Tenenbaum, J. B., and Ullman, T. D., “Modeling Expectation Violation in Intuitive Physics with Coarse Probabilistic Object Representations”, 33rd Conference on Neural Information Processing Systems (NeurIPS 2019). Vancouver, Canada, 2019.PDF icon ADEPT_NeurIPS.pdf (11.07 MB)
CBMM Funded
H. Stemmann and Freiwald, W. A., “Evidence for an attentional priority map in inferotemporal cortex”, Proceedings of the National Academy of Sciences, vol. 116, no. 47, pp. 23797 - 23805, 2019.
CBMM Related
C. Stephenson, Feather, J., Padhy, S., Elibol, O., Tang, H., McDermott, J. H., and Chung, S. Y., “Untangling in Invariant Speech Recognition”, Neural Information Processing Systems (NeurIPS 2019). Vancouver, Canada, 2019.PDF icon 9583-untangling-in-invariant-speech-recognition.pdf (2.09 MB)
CBMM Funded
L. A. Becker, Penagos, H., Manoach, D. S., Wilson, M. A., and Varela, C., “Disruption of CA1 Sharp-Wave Ripples by the nonbenzodiazepine hypnotic eszopiclone ”, in Society for Neuroscience, Chicago, IL, USA, 2019.
CBMM Funded
I. Dalla Betta, Cassara, A., Boyden, E. S., Brown, E. N., francisco,, and Flores, F. J., “In silico modeling of temporally interfering electric fields for deep brain stimulation ”, in Society for Neuroscience, Chicago, IL, USA, 2019.
CBMM Funded
J. Harrod, Purdon, P. L., Brown, E. N., and Flores, F. J., “Identification of vigilance states in freely behaving animals using thalamocortical activity and Deep Belief networks”, in Society for Neuroscience, 2019.
CBMM Funded
K. Kar and DiCarlo, J. J., “Evidence that recurrent pathways between the prefrontal and inferior temporal cortex is critical during core object recognition ”, in Society for Neuroscience, Chicago, IL, USA, 2019.
CBMM Funded
J. Kubilius, Schrimpf, M., Kar, K., Rajalingham, R., Hong, H., Majaj, N. J., Issa, E. B., Bashivan, P., Prescott-Roy, J., Schmidt, K., Nayebi, A., Bear, D., Yamins, D. L. K., and DiCarlo, J. J., “Brain-Like Object Recognition with High-Performing Shallow Recurrent ANNs”, 33rd Conference on Neural Information Processing Systems (NeurIPS 2019). Vancouver, Canada, 2019.PDF icon 2019-10-28 NeurIPS-camera_ready.pdf (1.88 MB)
CBMM Funded
K. Dobs, Palmer, I. A., Yuan, J., Mohsenzadeh, Y., Oliva, A., and Kanwisher, N., “Effects of Face Familiarity in Humans and Deep Neural Networks ”, in European Conference on Visual Perception, Leuven, Belgium, 2019.
CBMM Funded
S. J. Gershman, “The Generative Adversarial Brain”, Frontiers in Artificial Intelligence, vol. 2, 2019.
CBMM Related
N. Jacoby, Undurraga, E. A., McPherson, M. J., Valdés, J., Ossandón, T., and McDermott, J. H., “Universal and Non-universal Features of Musical Pitch Perception Revealed by Singing”, Current Biology, 2019.
CBMM Funded
A. J. E. Kell and McDermott, J. H., “Invariance to background noise as a signature of non-primary auditory cortex”, Nature Communications, vol. 10, no. 1, 2019.
CBMM Related
Q. Liao, Banburski, A., and Poggio, T., “Theories of Deep Learning: Approximation, Optimization and Generalization ”, TECHCON 2019. 2019.
CBMM Funded

Pages