Ashkan Khakzar

According to our database, Ashkan Khakzar authored at least 30 papers between 2017 and 2024.

Collaborative distances:

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

2024

A Survey on Transferability of Adversarial Examples Across Deep Neural Networks.

Jindong Gu, Xiaojun Jia, Pau de Jorge, Wenqian Yu, Xinwei Liu, Avery Ma, Yuan Xun, Anjun Hu, Ashkan Khakzar, Zhijiang Li, Xiaochun Cao, Philip Torr

Trans. Mach. Learn. Res., 2024

SafetyDPO: Scalable Safety Alignment for Text-to-Image Generation.

Runtao Liu, Chen I Chieh, Jindong Gu, Jipeng Zhang, Renjie Pi, Qifeng Chen, Philip Torr, Ashkan Khakzar, Fabio Pizzati

CoRR, 2024

Effortless Efficiency: Low-Cost Pruning of Diffusion Models.

Yang Zhang, Er Jin, Yanfei Dong, Ashkan Khakzar, Philip Torr, Johannes Stegmaier, Kenji Kawaguchi

CoRR, 2024

Hidden in Plain Sight: Evaluating Abstract Shape Recognition in Vision-Language Models.

Arshia Hemmat, Adam Davies, Tom A. Lamb, Jianhao Yuan, Philip Torr, Ashkan Khakzar, Francesco Pinto

CoRR, 2024

Sparse Autoencoders Reveal Universal Feature Spaces Across Large Language Models.

Michael Lan, Philip Torr, Austin Meek, Ashkan Khakzar, David Krueger, Fazl Barez

CoRR, 2024

The Cognitive Revolution in Interpretability: From Explaining Behavior to Interpreting Representations and Algorithms.

Adam Davies, Ashkan Khakzar

CoRR, 2024

Learning Visual Prompts for Guiding the Attention of Vision Transformers.

Razieh Rezaei, Masoud Jalili Sabet, Jindong Gu, Daniel Rueckert, Philip Torr, Ashkan Khakzar

CoRR, 2024

On Discprecncies between Perturbation Evaluations of Graph Neural Network Attributions.

Razieh Rezaei, Alireza Dizaji, Ashkan Khakzar, Anees Kazi, Nassir Navab, Daniel Rueckert

CoRR, 2024

Latent Guard: A Safety Framework for Text-to-Image Generation.

Runtao Liu, Ashkan Khakzar, Jindong Gu, Qifeng Chen, Philip Torr, Fabio Pizzati

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

Rethinking Feature Attribution for Neural Network Explanation.

Ashkan Khakzar

PhD thesis, 2023

AttributionLab: Faithfulness of Feature Attribution Under Controllable Environments.

Yang Zhang, Yawei Li, Hannah Brown, Mina Rezaei, Bernd Bischl, Philip H. S. Torr, Ashkan Khakzar, Kenji Kawaguchi

CoRR, 2023

A Dual-Perspective Approach to Evaluating Feature Attribution Methods.

Yawei Li, Yang Zhang, Kenji Kawaguchi, Ashkan Khakzar, Bernd Bischl, Mina Rezaei

CoRR, 2023

FlexR: Few-shot Classification with Language Embeddings for Structured Reporting of Chest X-rays.

Matthias Keicher, Kamilia Zaripova, Tobias Czempiel, Kristina Mach, Ashkan Khakzar, Nassir Navab

Proceedings of the Medical Imaging with Deep Learning, 2023

Pixel-Level Explanation of Multiple Instance Learning Models in Biomedical Single Cell Images.

Ario Sadafi, Oleksandra Adonkina, Ashkan Khakzar, Peter Lienemann, Rudolf Matthias Hehr, Daniel Rueckert, Nassir Navab, Carsten Marr

Proceedings of the Information Processing in Medical Imaging, 2023

2022

CheXplaining in Style: Counterfactual Explanations for Chest X-rays using StyleGAN.

Matan Atad, Vitalii Dmytrenko, Yitong Li, Xinyue Zhang, Matthias Keicher, Jan Kirschke, Benedikt Wiestler, Ashkan Khakzar, Nassir Navab

CoRR, 2022

Analyzing the Effects of Handling Data Imbalance on Learned Features from Medical Images by Looking Into the Models.

Ashkan Khakzar, Yawei Li, Yang Zhang, Mirac Sanisoglu, Seong Tae Kim, Mina Rezaei, Bernd Bischl, Nassir Navab

CoRR, 2022

Few-shot Structured Radiology Report Generation Using Natural Language Prompts.

Matthias Keicher, Kamilia Mullakaeva, Tobias Czempiel, Kristina Mach, Ashkan Khakzar, Nassir Navab

CoRR, 2022

Interpretable Vertebral Fracture Diagnosis.

Paul Engstler, Matthias Keicher, David Schinz, Kristina Mach, Alexandra S. Gersing, Sarah C. Foreman, Sophia S. Goller, Juergen Weissinger, Jon Rischewski, Anna-Sophia Dietrich, Benedikt Wiestler, Jan S. Kirschke, Ashkan Khakzar, Nassir Navab

Proceedings of the Interpretability of Machine Intelligence in Medical Image Computing, 2022

Do Explanations Explain? Model Knows Best.

Ashkan Khakzar, Pedram Khorsandi, Rozhin Nobahari, Nassir Navab

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Fine-Grained Neural Network Explanation by Identifying Input Features with Predictive Information.

Yang Zhang, Ashkan Khakzar, Yawei Li, Azade Farshad, Seong Tae Kim, Nassir Navab

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Longitudinal Quantitative Assessment of COVID-19 Infection Progression from Chest CTs.

Seong Tae Kim, Leili Goli, Magdalini Paschali, Ashkan Khakzar, Matthias Keicher, Tobias Czempiel, Egon Burian, Rickmer Braren, Nassir Navab, Thomas Wendler

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Explaining COVID-19 and Thoracic Pathology Model Predictions by Identifying Informative Input Features.

Ashkan Khakzar, Yang Zhang, Wejdene Mansour, Yuezhi Cai, Yawei Li, Yucheng Zhang, Seong Tae Kim, Nassir Navab

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Towards Semantic Interpretation of Thoracic Disease and COVID-19 Diagnosis Models.

Ashkan Khakzar, Sabrina Musatian, Jonas Buchberger, Icxel Valeriano Quiroz, Nikolaus Pinger, Soroosh Baselizadeh, Seong Tae Kim, Nassir Navab

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Neural Response Interpretation Through the Lens of Critical Pathways.

Ashkan Khakzar, Soroosh Baselizadeh, Saurabh Khanduja, Christian Rupprecht, Seong Tae Kim, Nassir Navab

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Rethinking Positive Aggregation and Propagation of Gradients in Gradient-based Saliency Methods.

Ashkan Khakzar, Soroosh Baselizadeh, Nassir Navab

CoRR, 2020

Spatio-Temporal Learning from Longitudinal Data for Multiple Sclerosis Lesion Segmentation.

Stefan Denner, Ashkan Khakzar, Moiz Sajid, Mahdi Saleh, Ziga Spiclin, Seong-Tae Kim, Nassir Navab

Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2020

2019

Explaining Neural Networks via Perturbing Important Learned Features.

Ashkan Khakzar, Soroosh Baselizadeh, Saurabh Khanduja, Seong Tae Kim, Nassir Navab

CoRR, 2019

Correction to: On the reproducibility of expert-operated and robotic ultrasound acquisitions.

Risto Kojcev, Ashkan Khakzar, Bernhard Fuerst, Oliver Zettinig, Carole Fakhry, Robert DeJong, Jeremy Richmon, Russell H. Taylor, Edoardo Sinibaldi, Nassir Navab

Int. J. Comput. Assist. Radiol. Surg., 2019

Learning Interpretable Features via Adversarially Robust Optimization.

Ashkan Khakzar, Shadi Albarqouni, Nassir Navab

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

2017

On the reproducibility of expert-operated and robotic ultrasound acquisitions.

Risto Kojcev, Ashkan Khakzar, Bernhard Fuerst, Oliver Zettinig, Carole Fahkry, Robert DeJong, Jeremy D. Richmon, Russell H. Taylor, Edoardo Sinibaldi, Nassir Navab

Int. J. Comput. Assist. Radiol. Surg., 2017