Haleh Akrami
Cited by
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A robust variational autoencoder using beta divergence
H Akrami, AA Joshi, J Li, S Aydore, RM Leahy
Knowledge-Based Systems, 107886, 2021
Lost in music: neural signature of pleasure and its role in modulating attentional resources
S Nemati, H Akrami, S Salehi, H Esteky, S Moghimi
Brain Research 1711, 7-15, 2019
Brain lesion detection using a robust variational autoencoder and transfer learning
H Akrami, AA Joshi, J Li, S Aydore, RM Leahy
2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 786-790, 2020
pSConv: A pre-defined sparse kernel based convolution for deep CNNs
S Kundu, S Prakash, H Akrami, PA Beerel, KM Chugg
2019 57th Annual Allerton Conference on Communication, Control, and …, 2019
Group-wise alignment of resting fMRI in space and time
H Akrami, AA Joshi, J Li, RM Leahy
Medical Imaging 2019: Image Processing 10949, 737-744, 2019
Robust variational autoencoder for tabular data with beta divergence
H Akrami, S Aydore, RM Leahy, AA Joshi
arXiv preprint arXiv:2006.08204, 2020
Addressing variance shrinkage in variational autoencoders using quantile regression
H Akrami, AA Joshi, S Aydore, RM Leahy
arXiv preprint arXiv:2010.09042, 2020
Culture modulates the brain response to harmonic violations: An EEG study on hierarchical syntactic structure in music
H Akrami, S Moghimi
Frontiers in Human Neuroscience 11, 591, 2017
Neuroanatomic Markers of Posttraumatic Epilepsy Based on MR Imaging and Machine Learning
H Akrami, RM Leahy, A Irimia, PE Kim, CN Heck, AA Joshi
American Journal of Neuroradiology 43 (3), 347-353, 2022
Quantile regression for uncertainty estimation in vaes with applications to brain lesion detection
H Akrami, A Joshi, S Aydore, R Leahy
International Conference on Information Processing in Medical Imaging, 689-700, 2021
Deep Quantile Regression for Uncertainty Estimation in Unsupervised and Supervised Lesion Detection
H Akrami, A Joshi, S Aydore, R Leahy
Machine Learning for Biomedical Imaging 1 (IPMI 2021 special issue), 1-10, 2022
A pairwise approach for fMRI group studies using the BrainSync Transform
AA Joshi, S Choi, J Li, H Akrami, RM Leahy
Medical imaging 2021: Image processing 11596, 96-102, 2021
Predicting cognitive scores from resting fMRI data and geometric features of the brain
AA Joshi, J Li, H Akrami, RM Leahy
Medical Imaging 2019: Image Processing 10949, 619-625, 2019
Semi-supervised Learning using Robust Loss
W Cui, H Akrami, A Joshi, R Leahy
Medical Imaging Meets NeurIPS Workshop, NeurIPS 2022, 2022
Prediction of posttraumatic epilepsy using machine learning
H Akrami, A Irimia, W Cui, AA Joshi, RM Leahy
Medical Imaging 2021: Biomedical Applications in Molecular, Structural, and …, 2021
Bias field correction in 3D-MRIs using convolutional autoencoders.
SN Sridhara, H Akrami, V Krishnamurthy, AA Joshi
Medical Imaging 2021: Image Processing 11596, 671-676, 2021
Robust variational autoencoder
A Haleh, A Joshi Anand, L Jian, M Leahy Richard
arXiv preprint arXiv:1905.09961, 2019
Meta transfer of self-supervised knowledge: Foundation model in action for post-traumatic epilepsy prediction
W Cui, H Akrami, G Zhao, AA Joshi, RM Leahy
arXiv preprint arXiv:2312.14204, 2023
Motor planning is not restricted to only one hemisphere: evidence from ERPs in individuals with hemiplegic cerebral palsy
N Sadeghi, MT Joghataei, A Shahbazi, SH Tonekaboni, H Akrami, ...
Experimental Brain Research 240 (9), 2311-2326, 2022
Learning from imperfect training data using a robust loss function: application to brain image segmentation
H Akrami, W Cui, AA Joshi, RM Leahy
arXiv preprint arXiv:2208.04941, 2022
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