Visualizing Deep Networks by Optimizing with Integrated Gradients. - Zhongang Qi; Saeed Khorram; Fuxin Li (AAAI, 2020)

Sleep Stage Scoring Using Joint Frequency-Temporal and Unsupervised Features. - Mohamadreza Jafaryani; Saeed Khorram; Vahid Pourahmadi; Minoo Shahbazi (CoRR, 2020)

Understanding Finite-State Representations of Recurrent Policy Networks. - Mohamad H. Danesh; Anurag Koul; Alan Fern; Saeed Khorram (CoRR, 2020)

iGOS++: integrated gradient optimized saliency by bilateral perturbations. - Saeed Khorram; Tyler Lawson; Fuxin Li (CHIL, 2021)

Re-understanding Finite-State Representations of Recurrent Policy Networks. - Mohamad H. Danesh; Anurag Koul; Alan Fern; Saeed Khorram (ICML, 2021)

Embedding deep networks into visual explanations. - Zhongang Qi; Saeed Khorram; Fuxin Li (Artif. Intell., 2021)

Stochastic Block-ADMM for Training Deep Networks. - Saeed Khorram; Xiao Fu; Mohamad H. Danesh; Zhongang Qi; Fuxin Li (CoRR, 2021)

From Heatmaps to Structural Explanations of Image Classifiers. - Fuxin Li; Zhongang Qi; Saeed Khorram; Vivswan Shitole; Prasad Tadepalli; Minsuk Kahng; Alan Fern (CoRR, 2021)

Cycle-Consistent Counterfactuals by Latent Transformations. - Saeed Khorram; Fuxin Li (CVPR, 2022)

Examining the Difference Among Transformers and CNNs with Explanation Methods. - Mingqi Jiang; Saeed Khorram; Fuxin Li (CoRR, 2022)

Diverse Explanations for Object Detectors with Nesterov-Accelerated iGOS++. - Mingqi Jiang; Saeed Khorram; Fuxin Li (BMVC, 2023)

Comparing the Decision-Making Mechanisms by Transformers and CNNs via Explanation Methods. - Mingqi Jiang; Saeed Khorram; Fuxin Li (CVPR, 2024)

Taming the Tail in Class-Conditional GANs: Knowledge Sharing via Unconditional Training at Lower Resolutions. - Saeed Khorram; Mingqi Jiang; Mohamad Shahbazi; Mohamad H. Danesh; Fuxin Li (CVPR, 2024)