| A robust variational autoencoder using beta divergence H Akrami, AA Joshi, J Li, S Aydore, RM Leahy Knowledge-Based Systems, 107886, 2021 | 63* | 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 | 32 | 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 | 25 | 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 | 18* | 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 | 17 | 2019 |
| Robust variational autoencoder for tabular data with beta divergence H Akrami, S Aydore, RM Leahy, AA Joshi arXiv preprint arXiv:2006.08204, 2020 | 16 | 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 | 9 | 2017 |
| 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 | 7 | 2022 |
| 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 | 7* | 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 | 7 | 2021 |
| Addressing variance shrinkage in variational autoencoders using quantile regression H Akrami, AA Joshi, S Aydore, RM Leahy arXiv preprint arXiv:2010.09042, 2020 | 6 | 2020 |
| 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 | 5 | 2019 |
| 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 | 4 | 2021 |
| 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 | 4 | 2021 |
| Semi-supervised Learning using Robust Loss W Cui, H Akrami, A Joshi, R Leahy Medical Imaging Meets NeurIPS Workshop, NeurIPS 2022, 2022 | 3 | 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 | 3 | 2021 |
| Robust variational autoencoder A Haleh, A Joshi Anand, L Jian, M Leahy Richard arXiv preprint arXiv:1905.09961, 2019 | 2 | 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, 2023 | 1 | 2023 |
| Learning From Positive and Unlabeled Data Using Observer-GAN O Zamzam, H Akrami, R Leahy ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 1 | 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 | 1 | 2022 |
Richard M. LeahyLeonard Silverman Chair in Electrical and Computer Engineering University of Southern CaliforniaVerified email at sipi.usc.edu
