no code implementations • 15 Nov 2023 • Salman Mohamadi, Donald A. Adjeroh
To our knowledge, along with identifying age-associated genes, this is the first work to propose a framework for computational causal inference on age-related genes, using a dataset of human dermal fibroblast gene expression data.
1 code implementation • 9 Jul 2023 • Salman Mohamadi, Ghulam Mujtaba, Ngan Le, Gianfranco Doretto, Donald A. Adjeroh
We also lay out essential foundational literature on LLMs and GAI in general and their connection with ChatGPT.
no code implementations • 2 Jul 2023 • Salman Mohamadi, Gianfranco Doretto, Donald A. Adjeroh
This paper is a fundamental work where, we investigate role of mutual information in SSL, and reformulate the problem of SSL in the context of a new perspective on mutual information.
no code implementations • 28 Oct 2022 • Salman Mohamadi, Gianfranco Doretto, Donald A. Adjeroh
This double supervision approach is captured in two key steps: 1) invariance enforcement to data augmentation, and 2) fuzzy pseudo labeling (both hard and soft annotation).
no code implementations • 11 Oct 2022 • Salman Mohamadi, Gianfranco Doretto, Donald A. Adjeroh
We show empirical results of our framework, and comparative performance with the state-of-the-art on four datasets, namely, MNIST, CIFAR10, CIFAR100 and ImageNet to establish a new baseline in two different settings.
no code implementations • 4 Nov 2021 • Salman Mohamadi, Donald Adjeroh
Investigation of age-related genes is of great importance for multiple purposes, for instance, improving our understanding of the mechanism of ageing, increasing life expectancy, age prediction, and other healthcare applications.
no code implementations • 4 Nov 2021 • Salman Mohamadi, Gianfranco. Doretto, Nasser M. Nasrabadi, Donald A. Adjeroh
In this line, we propose a new framework for human age estimation using information from human dermal fibroblast gene expression data.
no code implementations • 3 Aug 2021 • Moktari Mostofa, Salman Mohamadi, Jeremy Dawson, Nasser M. Nasrabadi
In the second approach, we design a coupled generative adversarial network (cpGAN) architecture consisting of a pair of cGAN modules that project the VIS and NIR iris images into a low-dimensional embedding domain to ensure maximum pairwise similarity between the feature vectors from the two iris modalities of the same subject.
no code implementations • 15 Dec 2020 • Salman Mohamadi, Hamidreza Amindavar
Deep Bayesian active learning frameworks and generally any Bayesian active learning settings, provide practical consideration in the model which allows training with small data while representing the model uncertainty for further efficient training.
no code implementations • 9 Aug 2019 • Salman Mohamadi, Farhang Yeganegi, Hamidreza Amindavar
This paper provides a framework in order to statistically model sequences from human genome, which is allowing a formulation to synthesize gene sequences.