Kailyn Schmidt
Kailyn Schmidt
Bestätigte E-Mail-Adresse bei mit.edu
Titel
Zitiert von
Zitiert von
Jahr
Large-scale, high-resolution comparison of the core visual object recognition behavior of humans, monkeys, and state-of-the-art deep artificial neural networks
R Rajalingham, EB Issa, P Bashivan, K Kar, K Schmidt, JJ DiCarlo
Journal of Neuroscience 38 (33), 7255-7269, 2018
1502018
Evidence that recurrent circuits are critical to the ventral stream’s execution of core object recognition behavior
K Kar, J Kubilius, K Schmidt, EB Issa, JJ DiCarlo
Nature neuroscience 22 (6), 974-983, 2019
1062019
Brain-score: Which artificial neural network for object recognition is most brain-like?
M Schrimpf, J Kubilius, H Hong, NJ Majaj, R Rajalingham, EB Issa, K Kar, ...
BioRxiv, 407007, 2018
692018
Comparison of object recognition behavior in human and monkey
R Rajalingham, K Schmidt, JJ DiCarlo
Journal of Neuroscience 35 (35), 12127-12136, 2015
622015
Brain-like object recognition with high-performing shallow recurrent ANNs
J Kubilius, M Schrimpf, K Kar, R Rajalingham, H Hong, N Majaj, E Issa, ...
Advances in Neural Information Processing Systems, 12805-12816, 2019
262019
Brain-Score: which artificial neural network for object recognition is most brain-like? bioRxiv
M Schrimpf, J Kubilius, H Hong, NJ Majaj, R Rajalingham, EB Issa, K Kar, ...
72018
Evidence that feedback is required for object identity inferences computed by the ventral stream
K Kar, J Kubilius, EB Issa, K Schmidt, JJ DiCarlo
Cosyne 17, Date: 2017/02/23-2017/02/26, Location: Salt Lake City (UT), USA, 2017
52017
Can deep neural networks rival human ability to generalize in core object recognition
J Kubilius, K Kar, KM Schmidt, JJ DiCarlo
Cognitive Computational Neuroscience, 2018a. URL https://ccneuro. org/2018 …, 2018
32018
Using brain-score to evaluate and build neural networks for brain-like object recognition
M Schrimpf, J Kubilius, H Hong, NJ Majaj, R Rajalingham, C Ziemba, ...
Cosyne 19, Date: 2019/02/28-2019/03/03, Location: Lisbon, Portugal, 2019
22019
Linking image-by-image population dynamics in the macaque inferior temporal cortex to core object recognition behavior
K Kar, KM Schmidt, JJ DiCarlo
Cognitive Computational Neuroscience, 2018b. URL https://ccneuro. org/2018 …, 0
1
Aligning Artificial Neural Networks to the Brain yields Shallow Recurrent Architectures
J Kubilius, M Schrimpf, H Hong, NJ Majaj, R Rajalingham, EB Issa, K Kar, ...
2018
Comparison of Object Recognition Behavior in Human and Monkey
R Rajalingham, K Schmidt, JJ DiCarlo
Journal of Vision 14 (10), 191-191, 2014
2014
Feedforward deep neural networks diverge from humans and monkeys on core visual object recognition behavior
R Rajalingham, EB Issa, K Schmidt, K Kar, JJ DiCarlo
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