Pouya Bashivan
Pouya Bashivan
Assistant Professor, McGill university
Geverifieerd e-mailadres voor mcgill.ca
Geciteerd door
Geciteerd door
Learning representations from EEG with deep recurrent-convolutional neural networks
P Bashivan, I Rish, M Yeasin, N Codella
arXiv preprint arXiv:1511.06448, 2015
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
Neural population control via deep image synthesis
P Bashivan, K Kar, JJ DiCarlo
Science 364 (6439), 2019
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, 2020
Brain-like object recognition with high-performing shallow recurrent ANNs
J Kubilius, M Schrimpf, K Kar, H Hong, NJ Majaj, R Rajalingham, EB Issa, ...
arXiv preprint arXiv:1909.06161, 2019
Spectrotemporal dynamics of the EEG during working memory encoding and maintenance predicts individual behavioral capacity
P Bashivan, GM Bidelman, M Yeasin
European Journal of Neuroscience 40 (12), 3774-3784, 2014
Mental State Recognition via Wearable EEG
P Bashivan, I Rish, S Heisig
Proceedings of 5th NIPS workshop on Machine Learning and Interpretation in …, 2015
Learning stable and predictive network-based patterns of schizophrenia and its clinical symptoms
M Gheiratmand, I Rish, GA Cecchi, MRG Brown, R Greiner, PI Polosecki, ...
NPJ schizophrenia 3 (1), 1-12, 2017
Learning neural markers of schizophrenia disorder using recurrent neural networks
J Dakka, P Bashivan, M Gheiratmand, I Rish, S Jha, R Greiner
arXiv preprint arXiv:1712.00512, 2017
Improved switching for multiple model adaptive controller in noisy environment
P Bashivan, A Fatehi
Journal of Process Control 22 (2), 390-396, 2012
Single trial prediction of normal and excessive cognitive load through EEG feature fusion
P Bashivan, M Yeasin, GM Bidelman
2015 IEEE Signal Processing in Medicine and Biology Symposium (SPMB), 1-5, 2015
An experimental comparison of adaptive controllers on a pH neutralization pilot plant
E Peymani, A Fatehi, P Bashivan, AK Sedigh
2008 Annual IEEE India Conference 2, 377-382, 2008
Teacher guided architecture search
P Bashivan, M Tensen, JJ DiCarlo
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
Neural correlates of visual working memory load through unsupervised spatial filtering of EEG
P Bashivan, GM Bidelman, M Yeasin
Proceedings of 3rd workshop on Machine Learning and Interpretation in …, 2013
Temporal progression in functional connectivity determines individual differences in working memory capacity
P Bashivan, M Yeasin, GM Bidelman
2017 International Joint Conference on Neural Networks (IJCNN), 2943-2949, 2017
A neurobiological evaluation metric for neural network model search
N Blanchard, J Kinnison, B RichardWebster, P Bashivan, WJ Scheirer
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
Single units in a deep neural network functionally correspond with neurons in the brain: preliminary results
L Arend, Y Han, M Schrimpf, P Bashivan, K Kar, T Poggio, JJ DiCarlo, ...
Center for Brains, Minds and Machines (CBMM), 2018
Multiple-model control of pH neutralization plant using the SOM neural networks
P Bashivan, A Fatehi, E Peymani
2008 Annual IEEE India Conference 1, 115-119, 2008
Evaluating effects of methylphenidate on brain activity in cocaine addiction: a machine-learning approach
I Rish, P Bashivan, GA Cecchi, RZ Goldstein
Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and …, 2016
Modulation of brain connectivity by memory load in a working memory network
P Bashivan, M Yeasin, GM Bidelman
2014 IEEE Symposium on Computational Intelligence, Cognitive Algorithms …, 2014
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