no code implementations • 8 Mar 2024 • Abdolmahdi Bagheri, Mahdi Dehshiri, Babak Nadjar Araabi, Alireza Akhondi Asl
In the investigation of any causal mechanisms, such as the brain's causal networks, the assumption of causal sufficiency plays a critical role.
1 code implementation • 28 Oct 2023 • Ali Javidani, Mohammad Amin Sadeghi, Babak Nadjar Araabi
To this end, we present a simple yet effective patch-matching algorithm that can find the corresponding patches across the augmented views.
no code implementations • 7 Sep 2023 • Abdolmahdi Bagheri, Mohammad Pasande, Kevin Bello, Babak Nadjar Araabi, Alireza Akhondi-Asl
However, learning DEC through these methods still faces two main challenges: one with the fundamental impotence of high-dimensional dynamic DAG discovery methods and the other with the low quality of fMRI data.
1 code implementation • 10 Feb 2023 • Abdolmahdi Bagheri, Mahdi Dehshiri, Yamin Bagheri, Alireza Akhondi-Asl, Babak Nadjar Araabi
By leveraging the DTI data as prior knowledge, we introduce two Bayesian causal discovery frameworks -- the Bayesian GOLEM (BGOLEM) and Bayesian FGES (BFGES) methods -- that offer significantly more accurate and reliable ECs and address the shortcomings of the existing causal discovery methods in discovering ECs based on only fMRI data.
1 code implementation • 11 Dec 2022 • Mohammad Pasande, Reshad Hosseini, Babak Nadjar Araabi
Gaussian Mixture Models (GMMs) are one of the most potent parametric density models used extensively in many applications.
1 code implementation • 27 Oct 2020 • Zahra Mousavi Kouzehkanan, Reshad Hosseini, Babak Nadjar Araabi
Many edge and contour detection algorithms give a soft-value as an output and the final binary map is commonly obtained by applying an optimal threshold.
no code implementations • 31 Mar 2020 • Saeed Masoudnia, Melika Kheirieh, Abdol-Hossein Vahabie, Babak Nadjar Araabi
In this paper, object-based attention in human visual cortex inspires us to introduce a mechanism for modification of activations in feature maps of CNNs.
no code implementations • 14 Apr 2017 • Mina Alibeigi, Majid Nili Ahmadabadi, Babak Nadjar Araabi
In ILoCI, observed multimodal spatio-temporal demonstrations are incrementally abstracted and generalized based on both their perceptual and functional similarities during the imitation.