Saeid Asgari Taghanaki

According to our database, Saeid Asgari Taghanaki authored at least 26 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

SMITE: Segment Me In TimE.

Amirhossein Alimohammadi, Sauradip Nag, Saeid Asgari Taghanaki, Andrea Tagliasacchi, Ghassan Hamarneh, Ali Mahdavi-Amiri

CoRR, 2024

MMLU-Pro+: Evaluating Higher-Order Reasoning and Shortcut Learning in LLMs.

Saeid Asgari Taghanaki, Ali Asghar Khani, Amir Khasahmadi

CoRR, 2024

How to Determine the Preferred Image Distribution of a Black-Box Vision-Language Model?

Saeid Asgari Taghanaki, Joseph G. Lambourne, Alana Mongkhounsavath

CoRR, 2024

Detecting Generative Parroting through Overfitting Masked Autoencoders.

Saeid Asgari Taghanaki, Joseph G. Lambourne

CoRR, 2024

SLiMe: Segment Like Me.

Aliasghar Khani, Saeid Asgari Taghanaki, Aditya Sanghi, Ali Mahdavi-Amiri, Ghassan Hamarneh

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Learned Visual Features to Textual Explanations.

Saeid Asgari Taghanaki, Aliasghar Khani, Amir Khasahmadi, Aditya Sanghi, Karl D. D. Willis, Ali Mahdavi-Amiri

CoRR, 2023

Sketch-A-Shape: Zero-Shot Sketch-to-3D Shape Generation.

Aditya Sanghi, Pradeep Kumar Jayaraman, Arianna Rampini, Joseph G. Lambourne, Hooman Shayani, Evan Atherton, Saeid Asgari Taghanaki

CoRR, 2023

2022

Counterbalancing Teacher: Regularizing Batch Normalized Models for Robustness.

Saeid Asgari Taghanaki, Ali Gholami, Fereshte Khani, Kristy Choi, Linh Tran, Ran Zhang, Aliasghar Khani

CoRR, 2022

MaskTune: Mitigating Spurious Correlations by Forcing to Explore.

Saeid Asgari Taghanaki, Aliasghar Khani, Fereshte Khani, Ali Gholami, Linh Tran, Ali Mahdavi-Amiri, Ghassan Hamarneh

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Group-disentangled Representation Learning with Weakly-Supervised Regularization.

Linh Tran, Amir Hosein Khasahmadi, Aditya Sanghi, Saeid Asgari Taghanaki

CoRR, 2021

Deep semantic segmentation of natural and medical images: a review.

Saeid Asgari Taghanaki, Kumar Abhishek, Joseph Paul Cohen, Julien Cohen-Adad, Ghassan Hamarneh

Artif. Intell. Rev., 2021

Robust Representation Learning via Perceptual Similarity Metrics.

Saeid Asgari Taghanaki, Kristy Choi, Amir Hosein Khasahmadi, Anirudh Goyal

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

RobustPointSet: A Dataset for Benchmarking Robustness of Point Cloud Classifiers.

Saeid Asgari Taghanaki, Jieliang Luo, Ran Zhang, Ye Wang, Pradeep Kumar Jayaraman, Krishna Murthy Jatavallabhula

CoRR, 2020

PointMask: Towards Interpretable and Bias-Resilient Point Cloud Processing.

Saeid Asgari Taghanaki, Kaveh Hassani, Pradeep Kumar Jayaraman, Amir Hosein Khas Ahmadi, Tonya Custis

CoRR, 2020

Jigsaw-VAE: Towards Balancing Features in Variational Autoencoders.

Saeid Asgari Taghanaki, Mohammad Havaei, Alex Lamb, Aditya Sanghi, Ara Danielyan, Tonya Custis

CoRR, 2020

2019

Signed Input Regularization.

Saeid Asgari Taghanaki, Kumar Abhishek, Ghassan Hamarneh

CoRR, 2019

Combo loss: Handling input and output imbalance in multi-organ segmentation.

Saeid Asgari Taghanaki, Yefeng Zheng, Shaohua Kevin Zhou, Bogdan Georgescu, Puneet Sharma, Daguang Xu, Dorin Comaniciu, Ghassan Hamarneh

Comput. Medical Imaging Graph., 2019

InfoMask: Masked Variational Latent Representation to Localize Chest Disease.

Saeid Asgari Taghanaki, Mohammad Havaei, Tess Berthier, Francis Dutil, Lisa Di-Jorio, Ghassan Hamarneh, Yoshua Bengio

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

Select, Attend, and Transfer: Light, Learnable Skip Connections.

Saeid Asgari Taghanaki, Aïcha BenTaieb, Anmol Sharma, Shaohua Kevin Zhou, Yefeng Zheng, Bogdan Georgescu, Puneet Sharma, Zhoubing Xu, Dorin Comaniciu, Ghassan Hamarneh

Proceedings of the Machine Learning in Medical Imaging - 10th International Workshop, 2019

Improved Inference via Deep Input Transfer.

Saeid Asgari Taghanaki, Kumar Abhishek, Ghassan Hamarneh

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

A Kernelized Manifold Mapping to Diminish the Effect of Adversarial Perturbations.

Saeid Asgari Taghanaki, Kumar Abhishek, Shekoofeh Azizi, Ghassan Hamarneh

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Select, Attend, and Transfer: Light, Learnable Skip Connections.

Saeid Asgari Taghanaki, Aïcha BenTaieb, Anmol Sharma, Shaohua Kevin Zhou, Yefeng Zheng, Bogdan Georgescu, Puneet Sharma, Sasa Grbic, Zhoubing Xu, Dorin Comaniciu, Ghassan Hamarneh

CoRR, 2018

Segmentation-free direct tumor volume and metabolic activity estimation from PET scans.

Saeid Asgari Taghanaki, Nóirín Duggan, Hillgan Ma, Xinchi Hou, Anna Celler, François Bénard, Ghassan Hamarneh

Comput. Medical Imaging Graph., 2018

Vulnerability Analysis of Chest X-Ray Image Classification Against Adversarial Attacks.

Saeid Asgari Taghanaki, Arkadeep Das, Ghassan Hamarneh

Proceedings of the Understanding and Interpreting Machine Learning in Medical Image Computing Applications, 2018

2017

Geometry-Based Pectoral Muscle Segmentation From MLO Mammogram Views.

Saeid Asgari Taghanaki, Yonghuai Liu, Brandon Miles, Ghassan Hamarneh

IEEE Trans. Biomed. Eng., 2017

Pareto-optimal multi-objective dimensionality reduction deep auto-encoder for mammography classification.

Saeid Asgari Taghanaki, Jeremy Kawahara, Brandon Miles, Ghassan Hamarneh

Comput. Methods Programs Biomed., 2017