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ORCIDHaleh Akrami
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2020 – today
- 2024
[c14]Haleh Akrami, Omar Zamzam, Anand A. Joshi, Sergül Aydöre, Richard M. Leahy:
Beta Quantile Regression for Robust Estimation of Uncertainty in the Presence of Outliers. ICASSP 2024: 7480-7484- 2023
- [c13]Haleh Akrami, Hannes Gamper:
Speech MOS Multi-Task Learning and Rater Bias Correction. ICASSP 2023: 1-5 - [c12]Omar Zamzam, Haleh Akrami, Richard M. Leahy:
Learning From Positive and Unlabeled Data Using Observer-GAN. ICASSP 2023: 1-5 - [i14]Haleh Akrami, Omar Zamzam, Anand A. Joshi, Sergül Aydöre, Richard M. Leahy:
Beta quantile regression for robust estimation of uncertainty in the presence of outliers. CoRR abs/2309.07374 (2023) - [i13]Omar Zamzam, Haleh Akrami, Mahdi Soltanolkotabi
, Richard M. Leahy:
Learning A Disentangling Representation For PU Learning. CoRR abs/2310.03833 (2023) - [i12]Wenhui Cui, Haleh Akrami, Ganning Zhao, Anand A. Joshi, Richard M. Leahy:
Meta Transfer of Self-Supervised Knowledge: Foundation Model in Action for Post-Traumatic Epilepsy Prediction. CoRR abs/2312.14204 (2023) - 2022
- [j1]Haleh Akrami, Anand A. Joshi, Jian Li, Sergül Aydöre, Richard M. Leahy:
A robust variational autoencoder using beta divergence. Knowl. Based Syst. 238: 107886 (2022) - [c11]Haleh Akrami, Tosha Shah, Amir Vajdi, Andrew Brown, Radha Krishnan, Razvan Cristescu, Antong Chen:
Sequential Multi-task Learning for Histopathology-Based Prediction of Genetic Mutations with Extremely Imbalanced Labels. MOVI@MICCAI 2022: 126-135 - [i11]Wenhui Cui, Haleh Akrami, Anand A. Joshi, Richard M. Leahy:
Semi-supervised Learning using Robust Loss. CoRR abs/2203.01524 (2022) - [i10]Haleh Akrami, Wenhui Cui, Anand A. Joshi, Richard M. Leahy:
Learning from imperfect training data using a robust loss function: application to brain image segmentation. CoRR abs/2208.04941 (2022) - [i9]Omar Zamzam, Haleh Akrami, Richard M. Leahy:
Learning From Positive and Unlabeled Data Using Observer-GAN. CoRR abs/2208.12477 (2022) - [i8]Haleh Akrami, Hannes Gamper:
Speech MOS multi-task learning and rater bias correction. CoRR abs/2212.01911 (2022) - [i7]Wenhui Cui, Haleh Akrami, Anand A. Joshi, Richard M. Leahy:
Toward Improved Generalization: Meta Transfer of Self-supervised Knowledge on Graphs. CoRR abs/2212.08217 (2022) - 2021
- [c10]Haleh Akrami, Anand A. Joshi, Sergül Aydöre, Richard M. Leahy:
Quantile Regression for Uncertainty Estimation in VAEs with Applications to Brain Lesion Detection. IPMI 2021: 689-700 - [c9]Haleh Akrami, Andrei Irimia, Wenhui Cui, Anand A. Joshi, Richard M. Leahy:
Prediction of posttraumatic epilepsy using machine learning. Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging 2021 - [c8]Anand A. Joshi, Soyoung Choi, Jian Li, Haleh Akrami, Richard M. Leahy:
A pairwise approach for fMRI group studies using the BrainSync Transform. Medical Imaging: Image Processing 2021 - [c7]Shashank N. Sridhara, Haleh Akrami, Vaishnavi Krishnamurthy, Anand A. Joshi:
Bias field correction in 3D-MRIs using convolutional autoencoders. Medical Imaging: Image Processing 2021 - [i6]Haleh Akrami, Anand A. Joshi, Sergül Aydöre, Richard M. Leahy:
Deep Quantile Regression for Uncertainty Estimation in Unsupervised and Supervised Lesion Detection. CoRR abs/2109.09374 (2021) - 2020
- [c6]Haleh Akrami, Anand A. Joshi, Jian Li, Sergül Aydöre, Richard M. Leahy:
Brain Lesion Detection Using A Robust Variational Autoencoder and Transfer Learning. ISBI 2020: 786-790 - [i5]Haleh Akrami, Sergül Aydöre, Richard M. Leahy, Anand A. Joshi:
Robust Variational Autoencoder for Tabular Data with Beta Divergence. CoRR abs/2006.08204 (2020) - [i4]Haleh Akrami, Anand A. Joshi, Sergül Aydöre, Richard M. Leahy:
Addressing Variance Shrinkage in Variational Autoencoders using Quantile Regression. CoRR abs/2010.09042 (2020) - [i3]Anand A. Joshi, Soyoung Choi, Haleh Akrami, Richard M. Leahy:
fMRI-Kernel Regression: A Kernel-based Method for Pointwise Statistical Analysis of rs-fMRI for Population Studies. CoRR abs/2012.06972 (2020)
2010 – 2019
- 2019
- [c5]Souvik Kundu, Saurav Prakash, Haleh Akrami, Peter A. Beerel, Keith M. Chugg:
pSConv: A Pre-defined S parse Kernel Based Convolution for Deep CNNs. Allerton 2019: 100-107 - [c4]Anand A. Joshi, Haleh Akrami, Jian Li, Richard M. Leahy:
A Matched Filter Decomposition of fMRI into Resting and Task Components. MICCAI (3) 2019: 673-681 - [c3]Haleh Akrami, Anand A. Joshi, Jian Li, Richard M. Leahy:
Group-wise alignment of resting fMRI in space and time. Medical Imaging: Image Processing 2019: 109492W - [c2]Anand A. Joshi, Jian Li, Haleh Akrami, Richard M. Leahy:
Predicting cognitive scores from resting fMRI data and geometric features of the brain. Medical Imaging: Image Processing 2019: 109492E - [i2]Haleh Akrami, Anand A. Joshi, Jian Li, Richard M. Leahy:
Robust Variational Autoencoder. CoRR abs/1905.09961 (2019) - [i1]Souvik Kundu, Saurav Prakash, Haleh Akrami, Peter A. Beerel, Keith M. Chugg:
A Pre-defined Sparse Kernel Based Convolution for Deep CNNs. CoRR abs/1910.00724 (2019) - 2018
- [c1]Anand A. Joshi, Jian Li, Minqi Chong, Haleh Akrami, Richard M. Leahy:
rfDemons: Resting fMRI-Based Cortical Surface Registration Using the BrainSync Transform. MICCAI (3) 2018: 198-205
Coauthor Index
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last updated on 2024-08-07 21:33 CEST by the dblp team
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