1 citations · 2 across the 7 of their papers we have counts for
7 papers
Beyond Augmentation: Leveraging Inter-Instance Relation in Self-Supervised Representation Learning
Ali Javidani, Babak Nadjar Araabi, Mohammad Amin Sadeghi
This paper introduces a novel approach that integrates graph theory into self-supervised representation learning. Traditional methods focus on intra-instance variations generated b…
Robustifying Diffusion-Denoised Smoothing Against Covariate Shift
Ali Hedayatnia, Mostafa Tavassolipour, Babak Nadjar Araabi +1
Randomized smoothing is a well-established method for achieving certified robustness against l2-adversarial perturbations. By incorporating a denoiser before the base classifier, p…
Enhancing Interpretability of Sparse Latent Representations with Class Information
Farshad Sangari Abiz, Reshad Hosseini, Babak N. Araabi
Variational Autoencoders (VAEs) are powerful generative models for learning latent representations. Standard VAEs generate dispersed and unstructured latent spaces by utilizing all…
DTFSal: Audio-Visual Dynamic Token Fusion for Video Saliency Prediction
Kiana Hooshanfar, Alireza Hosseini, Ahmad Kalhor +1
Audio-visual saliency prediction aims to mimic human visual attention by identifying salient regions in videos through the integration of both visual and auditory information. Alth…
From First-order to Higher-order Interactions: Enhanced Representation of Homotopic Functional Connectivity through Control of Intervening Variables
Behdad Khodabandehloo, Payam Jannatdoust, Babak Nadjar Araabi
The brain's complex functionality emerges from network interactions that go beyond dyadic connections, with higher-order interactions significantly contributing to this complexity.…
Algorithmic Identification of Essential Exogenous Nodes for Causal Sufficiency in Brain Networks
Abdolmahdi Bagheri, Mahdi Dehshiri, Babak Nadjar Araabi +1
In the investigation of any causal mechanisms, such as the brain's causal networks, the assumption of causal sufficiency plays a critical role. Notably, neglecting this assumption…
Patch-Wise Self-Supervised Visual Representation Learning: A Fine-Grained Approach
Ali Javidani, Mohammad Amin Sadeghi, Babak Nadjar Araabi
Self-supervised visual representation learning traditionally focuses on image-level instance discrimination. Our study introduces an innovative, fine-grained dimension by integrati…