How well do models of visual cortex generalize to out of distribution samples?.
Yifei Ren and Pouya Bashivan. BioRxiv

Using modular connectome-based predictive modeling to reveal brain-behavior relationships of individual differences in working memory.
Huayi Yang, Junjun Zhang, Zhenlan Jin, Pouya Bashivan and Ling Li. Brain Structure and Function

Towards out-of-distribution adversarial robustness.
Adam Ibrahim, Charles Guille-Escuret, Ioannis Mitliagkas, Irina Rish, David Krueger, Pouya Bashivan. arXiv

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

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

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

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

Teacher Guided Architecture Search
Bashivan P, Tensen M, DiCarlo J J ICCV .

Neural Population Control via Deep Image Synthesis
Bashivan P, Kar K, DiCarlo J J. Science.

Brain-like object recognition with high-performing shallow recurrent ANNs
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. NeurIPS.

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

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

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

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

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

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

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

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

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

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

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

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

Improved Switching for Multiple Model Adaptive Controller in Noisy Environment
Bashivan P and Fatehi A. Journal of Process Control.

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

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