Xaq Pitkow
Xaq Pitkow
Associate Professor of Computational Neuroscience, Baylor College of Medicine and Rice University
Verified email at rice.edu - Homepage
Cited by
Cited by
Information-limiting correlations
R Moreno-Bote, J Beck, I Kanitscheider, X Pitkow, P Latham, A Pouget
Nature neuroscience 17 (10), 1410-1417, 2014
Not noisy, just wrong: the role of suboptimal inference in behavioral variability
JM Beck, WJ Ma, X Pitkow, PE Latham, A Pouget
Neuron 74 (1), 30-39, 2012
Decorrelation and efficient coding by retinal ganglion cells
X Pitkow, M Meister
Nature neuroscience 15 (4), 628-635, 2012
Skip connections eliminate singularities
AE Orhan, X Pitkow
arXiv preprint arXiv:1701.09175, 2017
How can single sensory neurons predict behavior?
X Pitkow, S Liu, DE Angelaki, GC DeAngelis, A Pouget
Neuron 87 (2), 411-423, 2015
Engineering a less artificial intelligence
FH Sinz, X Pitkow, J Reimer, M Bethge, AS Tolias
Neuron 103 (6), 967-979, 2019
Inference in the brain: statistics flowing in redundant population codes
X Pitkow, DE Angelaki
Neuron 94 (5), 943-953, 2017
A neural computation for visual acuity in the presence of eye movements
X Pitkow, H Sompolinsky, M Meister
PLoS biology 5 (12), e331, 2007
A neural computation for visual acuity in the presence of eye movements
X Pitkow, H Sompolinsky, M Meister
PLoS biology 5 (12), e331, 2007
Inference in probabilistic graphical models by graph neural networks
KJ Yoon, R Liao, Y Xiong, L Zhang, E Fetaya, R Urtasun, R Zemel, ...
2019 53rd Asilomar Conference on Signals, Systems, and Computers, 868-875, 2019
Reviving and improving recurrent back-propagation
R Liao, Y Xiong, E Fetaya, L Zhang, KJ Yoon, X Pitkow, R Urtasun, ...
International Conference on Machine Learning, 3082-3091, 2018
Inception loops discover what excites neurons most using deep predictive models
EY Walker, FH Sinz, E Cobos, T Muhammad, E Froudarakis, PG Fahey, ...
Nature neuroscience 22 (12), 2060-2065, 2019
A simple approach to ignoring irrelevant variables by population decoding based on multisensory neurons
HGR Kim, X Pitkow, DE Angelaki, GC DeAngelis
Journal of neurophysiology 116 (3), 1449-1467, 2016
A dynamic Bayesian observer model reveals origins of bias in visual path integration
KJ Lakshminarasimhan, M Petsalis, H Park, GC DeAngelis, X Pitkow, ...
Neuron 99 (1), 194-206. e5, 2018
How the brain might work: Statistics flowing in redundant population codes
X Pitkow, D Angelaki
arXiv preprint arXiv:1702.03492, 2017
Exact feature probabilities in images with occlusion
X Pitkow
Journal of vision 10 (14), 42-42, 2010
Inference by reparameterization in neural population codes
R Vasudeva Raju, Z Pitkow
Advances in Neural Information Processing Systems 29, 2029-2037, 2016
Stimulus domain transfer in recurrent models for large scale cortical population prediction on video
FH Sinz, AS Ecker, PG Fahey, EY Walker, E Cobos, E Froudarakis, ...
bioRxiv, 452672, 2018
Faster processing of moving compared with flashed bars in awake macaque V1 provides a neural correlate of the flash lag illusion
M Subramaniyan, AS Ecker, SS Patel, RJ Cotton, M Bethge, X Pitkow, ...
Journal of neurophysiology 120 (5), 2430-2452, 2018
Learning from brains how to regularize machines
Z Li, W Brendel, EY Walker, E Cobos, T Muhammad, J Reimer, M Bethge, ...
arXiv preprint arXiv:1911.05072, 2019
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