Machine Learning- 2022

Pouya Bashivan, Adam Ibrahim, Amirozhan Dehghani, Yifei Ren, Learning Robust Kernel Ensembles with Kernel Average Poolingolore.

Neuroscience- 2021

N Apurva Ratan Murty, Pouya Bashivan, Alex Abate, James J DiCarlo, Nancy Kanwisher, Computational models of category-selective brain regions enable high-throughput tests of selectivity, Nature Communications.

Machine learning- 2021

Pouya Bashivan, Reza Bayat, Adam Ibrahim, Kartik Ahuja, Mojtaba Faramarzi, Touraj Laleh, Blake Aaron Richards, Irina Rish, Adversarial Feature Desensitization, NeurIPS.

Machine learning- 2019

N Blanchard, J Kinnison, B RichardWebster, P Bashivan, WJ Scheirer, A Neurobiological Evaluation Metric for Neural Network Model Search, Computer Vision and Pattern Recognition (CVPR).

Machine learning- 2019

Bashivan P, Tensen M, DiCarlo J J, Teacher Guided Architecture Search, International Conference on Computer Vision (ICCV).

Neuroscience- 2019

Schrimpf M, Kubilius J, Hong H, Majaj N J, Rajalingham R, Issa E B, Kar K, Bashivan P, Prescott-Roy J,Schmidt K, Yamins DLK, DiCarlo J J (2019), Brain-like object recognition with high-performing shallow recurrent ANNs, NeurIPS.

Machine learning- 2018

Bashivan P, Schrimpf M, Ajemian R, Rish I, Riemer M, Tu Y, Continual Learning with Self-Organizing Maps, NIPS Workshop on Continual Learning.

Neuroscience- 2018

Arend L, Han Y, Schrimpf M, Bashivan P, Kar K, Poggio T, DiCarlo JJ, Boix X. Single units in adeep neural network functionally correspond with neurons in the brain: preliminary results. Center for Brains, Minds and Machines (CBMM).

Neuroscience- 2018

Bashivan P, Kar K, DiCarlo J J, Neural Population Control via Deep ANN ImageSynthesis, Computational Cognitive Neuroscience Conference (CCN).

Neuroscience- 2018

Rajalingham R, Issa EB, Bashivan P, Kar K, Schmidt K, DiCarlo JJ, Large-scale, High-resolutionComparison of the core visual object recognition behavior of humans, monkeys, and state-of-the-art deep artificial neural networks, Journal of Neuroscience.

Neuroscience- 2017

Dakka J, Bashivan P, Gheiratmand M, Rish I, Jha S, Greiner R, Learning Neural Markers ofSchizophrenia Disorder Using Recurrent Neural Networks, NIPS workshop on Machine Learning for Health.

Neuroscience- 2017

Gheiratmand M, Rish I, Cecchi G, Brown M, Greiner R, Polosecki P, Bashivan P, Greenshaw A,Ramasubbu R, and Dursun R, Learning Stable and Predictive Network-based Patterns of Schizophrenia and its Clinical Symptoms, Nature Schizophrenia.

Neuroscience- 2017

Bashivan P, Yeasin M, Bidelman GM, Temporal Progression in Functional Connectivity DeterminesIndividual Differences in Working Memory Capacity, International Joint Conference on Neural Networks (IJCNN).

Machine learning- 2016

Bashivan P, Rish I, Yeasin M, Codella NC, Learning Representations from EEG with DeepRecurrent-Convolutional Neural Networks, International Conference on Learning Representations (ICLR).

Machine learning- 2015

Bashivan P, Rish I, Heisig S, Mental State Recognition via Wearable EEG, Proceedings of NIPSworkshop on Machine Learning and Interpretation in Neuroimaging (MLINI15).

Machine learning- 2015

Bashivan P, Yeasin M, Bidelman GM, Single trial prediction of normal and excessive cognitive loadthrough EEG feature fusion, Proceedings of IEEE Signal Processing in Medicine and Biology (SPMB).

Neuroscience- 2014

Bashivan P, Bidelman GM, Yeasin M, Modulation of Brain Connectivity by Memory Load in a Working Memory Network, Proceedings of IEEE Symposium Series on Computational Intelligence (SSCI).

Neuroscience- 2014

Bashivan P, Bidelman GM, Yeasin M, Spectrotemporal dynamics of the EEG during workingmemory encoding and maintenance predicts individual behavioral capacity, Eur. Journal of Neuroscience.

Machine learning- 2013

Bashivan P, Bidelman GM, Yeasin M, Neural correlates of visual working memory load throughunsupervised spatial filtering of EEG, Proceedings of NIPS workshop on Machine Learning and Interpretation in Neuroimaging (MLINI13).

Control engineering- 2008

Bashivan P, Fatehi A, Peymani E, Multiple-model control of pH neutralization plant using the SOM neural networks, Proceedings of IEEE Conference on Control, Communication and Automation (INDICON).

Control engineering- 2008

Peymani E, Fatehi A, Bashivan P, and Khaki–Sedigh A, An Experimental Comparison of Adaptive Controllers on a pH Neutralization Pilot Plant, Proceedings of IEEE Conference on Control, Communication and Automation (INDICON).