rfDemons: Resting fMRI-Based Cortical Surface Registration Using the BrainSync Transform. - Anand A. Joshi; Jian Li 033; Minqi Chong; Haleh Akrami; Richard M. Leahy (MICCAI (3), 2018)

pSConv: A Pre-defined S parse Kernel Based Convolution for Deep CNNs. - Souvik Kundu 002; Saurav Prakash; Haleh Akrami; Peter A. Beerel; Keith M. Chugg (Allerton, 2019)

A Matched Filter Decomposition of fMRI into Resting and Task Components. - Anand A. Joshi; Haleh Akrami; Jian Li 033; Richard M. Leahy (MICCAI (3), 2019)

Group-wise alignment of resting fMRI in space and time. - Haleh Akrami; Anand A. Joshi; Jian Li 033; Richard M. Leahy (Image Processing, 2019)

Predicting cognitive scores from resting fMRI data and geometric features of the brain. - Anand A. Joshi; Jian Li 033; Haleh Akrami; Richard M. Leahy (Image Processing, 2019)

Robust Variational Autoencoder. - Haleh Akrami; Anand A. Joshi; Jian Li 033; Richard M. Leahy (CoRR, 2019)

A Pre-defined Sparse Kernel Based Convolution for Deep CNNs. - Souvik Kundu 002; Saurav Prakash; Haleh Akrami; Peter A. Beerel; Keith M. Chugg (CoRR, 2019)

Brain Lesion Detection Using A Robust Variational Autoencoder and Transfer Learning. - Haleh Akrami; Anand A. Joshi; Jian Li 033; Sergül Aydöre; Richard M. Leahy (ISBI, 2020)

Robust Variational Autoencoder for Tabular Data with Beta Divergence. - Haleh Akrami; Sergül Aydöre; Richard M. Leahy; Anand A. Joshi (CoRR, 2020)

Addressing Variance Shrinkage in Variational Autoencoders using Quantile Regression. - Haleh Akrami; Anand A. Joshi; Sergül Aydöre; Richard M. Leahy (CoRR, 2020)

fMRI-Kernel Regression: A Kernel-based Method for Pointwise Statistical Analysis of rs-fMRI for Population Studies. - Anand A. Joshi; Soyoung Choi; Haleh Akrami; Richard M. Leahy (CoRR, 2020)

Quantile Regression for Uncertainty Estimation in VAEs with Applications to Brain Lesion Detection. - Haleh Akrami; Anand A. Joshi; Sergül Aydöre; Richard M. Leahy (IPMI, 2021)

Prediction of posttraumatic epilepsy using machine learning. - Haleh Akrami; Andrei Irimia; Wenhui Cui; Anand A. Joshi; Richard M. Leahy (Biomedical Applications in Molecular, Structural, and Functional Imaging, 2021)

A pairwise approach for fMRI group studies using the BrainSync Transform. - Anand A. Joshi; Soyoung Choi; Jian Li 033; Haleh Akrami; Richard M. Leahy (Image Processing, 2021)

Bias field correction in 3D-MRIs using convolutional autoencoders. - Shashank N. Sridhara; Haleh Akrami; Vaishnavi Krishnamurthy; Anand A. Joshi (Image Processing, 2021)

Deep Quantile Regression for Uncertainty Estimation in Unsupervised and Supervised Lesion Detection. - Haleh Akrami; Anand A. Joshi; Sergül Aydöre; Richard M. Leahy (CoRR, 2021)

Sequential Multi-task Learning for Histopathology-Based Prediction of Genetic Mutations with Extremely Imbalanced Labels. - Haleh Akrami; Tosha Shah; Amir Vajdi; Andrew Brown; Radha Krishnan; Razvan Cristescu; Antong Chen (MOVI@MICCAI, 2022)

Prediction of tumor mutation burden from H&E whole-slide images: a comparison of training strategies with convolutional neural networks. - Antong Chen; Tosha Shah; Andrew Brown; Haleh Akrami; Albert Swiston; Amir Vajdi; Radha Krishnan; Razvan Cristescu (Digital and Computational Pathology, 2022)

Semi-supervised Learning using Robust Loss. - Wenhui Cui; Haleh Akrami; Anand A. Joshi; Richard M. Leahy (CoRR, 2022)

Learning from imperfect training data using a robust loss function: application to brain image segmentation. - Haleh Akrami; Wenhui Cui; Anand A. Joshi; Richard M. Leahy (CoRR, 2022)

Toward Improved Generalization: Meta Transfer of Self-supervised Knowledge on Graphs. - Wenhui Cui; Haleh Akrami; Anand A. Joshi; Richard M. Leahy (CoRR, 2022)

A robust variational autoencoder using beta divergence. - Haleh Akrami; Anand A. Joshi; Jian Li 033; Sergül Aydöre; Richard M. Leahy (Knowl. Based Syst., 2022)

Speech MOS Multi-Task Learning and Rater Bias Correction. - Haleh Akrami; Hannes Gamper (ICASSP, 2023)

Learning From Positive and Unlabeled Data Using Observer-GAN. - Omar Zamzam; Haleh Akrami; Richard M. Leahy (ICASSP, 2023)

Learning A Disentangling Representation For PU Learning. - Omar Zamzam; Haleh Akrami; Mahdi Soltanolkotabi; Richard M. Leahy (CoRR, 2023)

Meta Transfer of Self-Supervised Knowledge: Foundation Model in Action for Post-Traumatic Epilepsy Prediction. - Wenhui Cui; Haleh Akrami; Ganning Zhao; Anand A. Joshi; Richard M. Leahy (CoRR, 2023)

Beta Quantile Regression for Robust Estimation of Uncertainty in the Presence of Outliers. - Haleh Akrami; Omar Zamzam; Anand A. Joshi; Sergül Aydöre; Richard M. Leahy (ICASSP, 2024)

Generalizable Representation Learning for fMRI-based Neurological Disorder Identification. - Wenhui Cui; Haleh Akrami; Anand A. Joshi; Richard M. Leahy (Trans. Mach. Learn. Res., 2025)

Modeling and Reversing Brain Lesions Using Diffusion Models. - Omar Zamzam; Haleh Akrami; Anand A. Joshi; Richard M. Leahy (CoRR, 2025)