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Lane Thomas McIntosh
Lane Thomas McIntosh
PhD Candidate, Stanford University
Verified email at stanford.edu - Homepage
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 29, 2016
231*2016
The dynamic neural code of the retina for natural scenes
N Maheswaranathan, LT McIntosh, H Tanaka, S Grant, DB Kastner, ...
BioRxiv, 340943, 2019
432019
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
382019
Recurrent segmentation for variable computational budgets
L McIntosh, N Maheswaranathan, D Sussillo, J Shlens
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
222018
Advances in neural information processing systems
L McIntosh, N Maheswaranathan, A Nayebi, S Ganguli, S Baccus, D Lee, ...
Curran, Red Hook, NY 29, 1369-1377, 2016
132016
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
112018
Deep learning models reveal internal structure and diverse computations in the retina under natural scenes. bioRxiv, 340943
N Maheswaranathan, LT McIntosh, DB Kastner, J Melander, L Brezovec, ...
62018
Synchronous inhibitory pathways create both efficiency and diversity in the retina
M Manu, LT McIntosh, DB Kastner, BN Naecker, SA Baccus
biorxiv, 214569, 2017
22017
Information Processing and Energy Dissipation in Neurons
L McIntosh
University of Hawaii at Manoa, 2012
12012
Synchronous inhibitory pathways create both efficiency and diversity in the retina
M Manu, LT McIntosh, DB Kastner, BN Naecker, SA Baccus
Proceedings of the National Academy of Sciences 119 (4), e2116589119, 2022
2022
A mechanistically interpretable model of the retinal neural code for natural scenes with multiscale adaptive dynamics
X Ding, D Lee, S Grant, H Stein, L McIntosh, N Maheswaranathan, ...
2021 55th Asilomar Conference on Signals, Systems, and Computers, 287-291, 2021
2021
Revealing computational mechanisms of retinal prediction via model reduction
H Tanaka, A Nayebi, N Maheswaranathan, L McIntosh, SA Baccus, ...
2019
Understanding Early Vision: From White Noise to Natural Scenes
L McIntosh
Stanford University, 2018
2018
Video-Based Event Recognition!
I Ballard, L McIntosh
Learning Predictive Filters
L McIntosh
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Articles 1–15