Follow
Aran Nayebi
Title
Cited by
Cited by
Year
Deep Learning Models of the Retinal Response to Natural Scenes
L McIntosh, N Maheswaranathan, A Nayebi, S Ganguli, S Baccus
Advances in Neural Information Processing Systems (NIPS 2016) 29, 1369--1377, 2016
1882016
Task-driven convolutional recurrent models of the visual system
A Nayebi, D Bear, J Kubilius, K Kar, S Ganguli, D Sussillo, JJ DiCarlo, ...
Advances in neural information processing systems 31, 2018
1112018
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 32, 2019
1092019
Unsupervised neural network models of the ventral visual stream
C Zhuang, S Yan, A Nayebi, M Schrimpf, MC Frank, JJ DiCarlo, ...
Proceedings of the National Academy of Sciences 118 (3), 2021
942021
Biologically inspired protection of deep networks from adversarial attacks
A Nayebi, S Ganguli
arXiv preprint arXiv:1703.09202, 2017
932017
CORnet: modeling the neural mechanisms of core object recognition
J Kubilius, M Schrimpf, A Nayebi, D Bear, DLK Yamins, JJ DiCarlo
BioRxiv, 408385, 2018
812018
Gruv: Algorithmic music generation using recurrent neural networks
A Nayebi, M Vitelli
Course CS224D: Deep Learning for Natural Language Processing (Stanford), 2015
422015
The dynamic neural code of the retina for natural scenes
N Maheswaranathan, LT McIntosh, H Tanaka, S Grant, DB Kastner, ...
BioRxiv, 340943, 2019
392019
Learning physical graph representations from visual scenes
D Bear, C Fan, D Mrowca, Y Li, S Alter, A Nayebi, J Schwartz, LF Fei-Fei, ...
Advances in Neural Information Processing Systems 33, 6027-6039, 2020
342020
From deep learning to mechanistic understanding in neuroscience: the structure of retinal prediction
H Tanaka, A Nayebi, N Maheswaranathan, L McIntosh, S Baccus, ...
Advances in neural information processing systems 32, 2019
342019
Carma: A deep reinforcement learning approach to autonomous driving
M Vitelli, A Nayebi
Tech. rep. Stanford University, Tech. Rep., 2016
272016
Two routes to scalable credit assignment without weight symmetry
D Kunin, A Nayebi, J Sagastuy-Brena, S Ganguli, J Bloom, D Yamins
International Conference on Machine Learning, 5511-5521, 2020
182020
Deep learning models reveal internal structure and diverse computations in the retina under natural scenes. bioRxiv
N Maheswaranathan, LT McIntosh, DB Kastner, J Melander, L Brezovec, ...
URL: https://www. biorxiv. org/content/early/2018/06/14/340943. http://dx …, 2018
172018
Quantum lower bound for inverting a permutation with advice
A Nayebi, S Aaronson, A Belovs, L Trevisan
arXiv preprint arXiv:1408.3193, 2014
132014
Fast matrix multiplication techniques based on the Adleman-Lipton model
A Nayebi
arXiv preprint arXiv:0912.0750, 2009
102009
Goal-driven recurrent neural network models of the ventral visual stream
A Nayebi, J Sagastuy-Brena, DM Bear, K Kar, J Kubilius, S Ganguli, ...
bioRxiv, 2021
92021
Cornet: Modeling the neural mechanisms of core object recognition. BioRxiv, 408385
J Kubilius, M Schrimpf, A Nayebi, D Bear, DLK Yamins, JJ DiCarlo
92018
Quantum algorithms for shortest paths problems in structured instances
A Nayebi, VV Williams
arXiv preprint arXiv:1410.6220, 2014
82014
Identifying learning rules from neural network observables
A Nayebi, S Srivastava, S Ganguli, DL Yamins
Advances in Neural Information Processing Systems 33, 2639-2650, 2020
72020
Segment Extension Based on Lookalike Selection
K Modarresi, I Radu, C Menguy, JV Muthiyil, Y Liu, S Qiang, A Nayebi
US Patent App. 15/700,343, 2019
72019
The system can't perform the operation now. Try again later.
Articles 1–20