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ORCIDAshkan Khakzar
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2020 – today
- 2025
[i27]Xingyi Yang, Constantin Venhoff, Ashkan Khakzar, Christian Schröder de Witt, Puneet K. Dokania, Adel Bibi, Philip Torr:
Mixture of Experts Made Intrinsically Interpretable. CoRR abs/2503.07639 (2025)- 2024
- [j3]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:
A Survey on Transferability of Adversarial Examples Across Deep Neural Networks. Trans. Mach. Learn. Res. 2024 (2024) - [c13]Runtao Liu, Ashkan Khakzar, Jindong Gu, Qifeng Chen, Philip Torr, Fabio Pizzati:
Latent Guard: A Safety Framework for Text-to-Image Generation. ECCV (26) 2024: 93-109 - [c12]Arshia Hemmat, Adam Davies, Tom A. Lamb, Jianhao Yuan, Philip Torr, Ashkan Khakzar, Francesco Pinto:
Hidden in Plain Sight: Evaluating Abstract Shape Recognition in Vision-Language Models. NeurIPS 2024 - [i26]Razieh Rezaei, Alireza Dizaji, Ashkan Khakzar, Anees Kazi, Nassir Navab, Daniel Rueckert:
On Discprecncies between Perturbation Evaluations of Graph Neural Network Attributions. CoRR abs/2401.00633 (2024) - [i25]Runtao Liu, Ashkan Khakzar, Jindong Gu, Qifeng Chen, Philip Torr, Fabio Pizzati:
Latent Guard: a Safety Framework for Text-to-image Generation. CoRR abs/2404.08031 (2024) - [i24]Razieh Rezaei, Masoud Jalili Sabet, Jindong Gu, Daniel Rueckert, Philip Torr, Ashkan Khakzar:
Learning Visual Prompts for Guiding the Attention of Vision Transformers. CoRR abs/2406.03303 (2024) - [i23]Adam Davies, Ashkan Khakzar:
The Cognitive Revolution in Interpretability: From Explaining Behavior to Interpreting Representations and Algorithms. CoRR abs/2408.05859 (2024) - [i22]Michael Lan, Philip Torr, Austin Meek, Ashkan Khakzar, David Krueger, Fazl Barez:
Sparse Autoencoders Reveal Universal Feature Spaces Across Large Language Models. CoRR abs/2410.06981 (2024) - [i21]Arshia Hemmat, Adam Davies, Tom A. Lamb, Jianhao Yuan, Philip Torr, Ashkan Khakzar, Francesco Pinto:
Hidden in Plain Sight: Evaluating Abstract Shape Recognition in Vision-Language Models. CoRR abs/2411.06287 (2024) - [i20]Yang Zhang, Er Jin, Yanfei Dong, Ashkan Khakzar, Philip Torr, Johannes Stegmaier, Kenji Kawaguchi:
Effortless Efficiency: Low-Cost Pruning of Diffusion Models. CoRR abs/2412.02852 (2024) - [i19]Runtao Liu, Chen I Chieh, Jindong Gu, Jipeng Zhang, Renjie Pi, Qifeng Chen, Philip Torr, Ashkan Khakzar, Fabio Pizzati:
SafetyDPO: Scalable Safety Alignment for Text-to-Image Generation. CoRR abs/2412.10493 (2024) - 2023
- [b1]Ashkan Khakzar:
Rethinking Feature Attribution for Neural Network Explanation. Technical University of Munich, Germany, 2023 - [c11]Ario Sadafi, Oleksandra Adonkina, Ashkan Khakzar, Peter Lienemann, Rudolf Matthias Hehr, Daniel Rueckert, Nassir Navab, Carsten Marr:
Pixel-Level Explanation of Multiple Instance Learning Models in Biomedical Single Cell Images. IPMI 2023: 170-182 - [c10]Matthias Keicher, Kamilia Zaripova, Tobias Czempiel, Kristina Mach, Ashkan Khakzar, Nassir Navab:
FlexR: Few-shot Classification with Language Embeddings for Structured Reporting of Chest X-rays. MIDL 2023: 1493-1508 - [i18]Ario Sadafi, Oleksandra Adonkina, Ashkan Khakzar, Peter Lienemann, Rudolf Matthias Hehr, Daniel Rueckert, Nassir Navab, Carsten Marr:
Pixel-Level Explanation of Multiple Instance Learning Models in Biomedical Single Cell Images. CoRR abs/2303.08632 (2023) - [i17]Yawei Li, Yang Zhang, Kenji Kawaguchi, Ashkan Khakzar, Bernd Bischl, Mina Rezaei:
A Dual-Perspective Approach to Evaluating Feature Attribution Methods. CoRR abs/2308.08949 (2023) - [i16]Yang Zhang, Yawei Li, Hannah Brown, Mina Rezaei, Bernd Bischl, Philip H. S. Torr, Ashkan Khakzar, Kenji Kawaguchi:
AttributionLab: Faithfulness of Feature Attribution Under Controllable Environments. CoRR abs/2310.06514 (2023) - [i15]Jindong Gu, Xiaojun Jia, Pau de Jorge, Wenqian Yu, Xinwei Liu, Avery Ma, Yuan Xun, Anjun Hu, Ashkan Khakzar, Zhijiang Li, Xiaochun Cao, Philip H. S. Torr:
A Survey on Transferability of Adversarial Examples across Deep Neural Networks. CoRR abs/2310.17626 (2023) - 2022
- [c9]Ashkan Khakzar, Pedram Khorsandi, Rozhin Nobahari, Nassir Navab:
Do Explanations Explain? Model Knows Best. CVPR 2022: 10234-10243 - [c8]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:
Interpretable Vertebral Fracture Diagnosis. iMIMIC@MICCAI 2022: 71-81 - [i14]Ashkan Khakzar, Pedram Khorsandi, Rozhin Nobahari, Nassir Navab:
Do Explanations Explain? Model Knows Best. CoRR abs/2203.02269 (2022) - [i13]Matthias Keicher, Kamilia Mullakaeva, Tobias Czempiel, Kristina Mach, Ashkan Khakzar, Nassir Navab:
Few-shot Structured Radiology Report Generation Using Natural Language Prompts. CoRR abs/2203.15723 (2022) - [i12]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:
Interpretable Vertebral Fracture Diagnosis. CoRR abs/2203.16273 (2022) - [i11]Ashkan Khakzar, Yawei Li, Yang Zhang, Mirac Sanisoglu, Seong Tae Kim, Mina Rezaei, Bernd Bischl, Nassir Navab:
Analyzing the Effects of Handling Data Imbalance on Learned Features from Medical Images by Looking Into the Models. CoRR abs/2204.01729 (2022) - [i10]Matan Atad, Vitalii Dmytrenko, Yitong Li
, Xinyue Zhang, Matthias Keicher, Jan Kirschke, Benedikt Wiestler, Ashkan Khakzar, Nassir Navab:
CheXplaining in Style: Counterfactual Explanations for Chest X-rays using StyleGAN. CoRR abs/2207.07553 (2022) - 2021
- [c7]Ashkan Khakzar, Soroosh Baselizadeh, Saurabh Khanduja, Christian Rupprecht, Seong Tae Kim, Nassir Navab:
Neural Response Interpretation Through the Lens of Critical Pathways. CVPR 2021: 13528-13538 - [c6]Seong Tae Kim, Leili Goli, Magdalini Paschali, Ashkan Khakzar, Matthias Keicher, Tobias Czempiel, Egon Burian, Rickmer Braren, Nassir Navab, Thomas Wendler:
Longitudinal Quantitative Assessment of COVID-19 Infection Progression from Chest CTs. MICCAI (7) 2021: 273-282 - [c5]Ashkan Khakzar, Yang Zhang, Wejdene Mansour, Yuezhi Cai, Yawei Li, Yucheng Zhang, Seong Tae Kim, Nassir Navab:
Explaining COVID-19 and Thoracic Pathology Model Predictions by Identifying Informative Input Features. MICCAI (3) 2021: 391-401 - [c4]Ashkan Khakzar, Sabrina Musatian, Jonas Buchberger, Icxel Valeriano Quiroz, Nikolaus Pinger, Soroosh Baselizadeh, Seong Tae Kim, Nassir Navab:
Towards Semantic Interpretation of Thoracic Disease and COVID-19 Diagnosis Models. MICCAI (3) 2021: 499-508 - [c3]Yang Zhang, Ashkan Khakzar, Yawei Li, Azade Farshad, Seong Tae Kim, Nassir Navab:
Fine-Grained Neural Network Explanation by Identifying Input Features with Predictive Information. NeurIPS 2021: 20040-20051 - [i9]Seong-Tae Kim, Leili Goli, Magdalini Paschali, Ashkan Khakzar, Matthias Keicher, Tobias Czempiel, Egon Burian, Rickmer Braren, Nassir Navab, Thomas Wendler:
Longitudinal Quantitative Assessment of COVID-19 Infection Progression from Chest CTs. CoRR abs/2103.07240 (2021) - [i8]Ashkan Khakzar, Soroosh Baselizadeh, Saurabh Khanduja, Christian Rupprecht, Seong Tae Kim, Nassir Navab:
Neural Response Interpretation through the Lens of Critical Pathways. CoRR abs/2103.16886 (2021) - [i7]Ashkan Khakzar, Yang Zhang, Wejdene Mansour, Yuezhi Cai, Yawei Li, Yucheng Zhang, Seong Tae Kim, Nassir Navab:
Explaining COVID-19 and Thoracic Pathology Model Predictions by Identifying Informative Input Features. CoRR abs/2104.00411 (2021) - [i6]Ashkan Khakzar, Sabrina Musatian, Jonas Buchberger, Icxel Valeriano Quiroz, Nikolaus Pinger, Soroosh Baselizadeh, Seong Tae Kim, Nassir Navab:
Towards Semantic Interpretation of Thoracic Disease and COVID-19 Diagnosis Models. CoRR abs/2104.02481 (2021) - [i5]Yang Zhang, Ashkan Khakzar, Yawei Li, Azade Farshad, Seong Tae Kim, Nassir Navab:
Fine-Grained Neural Network Explanation by Identifying Input Features with Predictive Information. CoRR abs/2110.01471 (2021) - 2020
- [c2]Stefan Denner, Ashkan Khakzar, Moiz Sajid, Mahdi Saleh, Ziga Spiclin, Seong-Tae Kim, Nassir Navab:
Spatio-Temporal Learning from Longitudinal Data for Multiple Sclerosis Lesion Segmentation. BrainLes@MICCAI (1) 2020: 111-121 - [i4]Stefan Denner, Ashkan Khakzar, Moiz Sajid, Mahdi Saleh, Ziga Spiclin, Seong Tae Kim, Nassir Navab:
Spatio-temporal Learning from Longitudinal Data for Multiple Sclerosis Lesion Segmentation. CoRR abs/2004.03675 (2020) - [i3]Ashkan Khakzar, Soroosh Baselizadeh, Nassir Navab:
Rethinking Positive Aggregation and Propagation of Gradients in Gradient-based Saliency Methods. CoRR abs/2012.00362 (2020)
2010 – 2019
- 2019
- [j2]Risto Kojcev, Ashkan Khakzar, Bernhard Fuerst, Oliver Zettinig, Carole Fakhry, Robert DeJong, Jeremy Richmon, Russell H. Taylor, Edoardo Sinibaldi, Nassir Navab:
Correction to: On the reproducibility of expert-operated and robotic ultrasound acquisitions. Int. J. Comput. Assist. Radiol. Surg. 14(10): 1821 (2019) - [c1]Ashkan Khakzar, Shadi Albarqouni, Nassir Navab:
Learning Interpretable Features via Adversarially Robust Optimization. MICCAI (6) 2019: 793-800 - [i2]Ashkan Khakzar, Shadi Albarqouni, Nassir Navab:
Learning Interpretable Features via Adversarially Robust Optimization. CoRR abs/1905.03767 (2019) - [i1]Ashkan Khakzar, Soroosh Baselizadeh, Saurabh Khanduja, Seong Tae Kim, Nassir Navab:
Explaining Neural Networks via Perturbing Important Learned Features. CoRR abs/1911.11081 (2019) - 2017
- [j1]Risto Kojcev, Ashkan Khakzar, Bernhard Fuerst, Oliver Zettinig, Carole Fahkry, Robert DeJong, Jeremy D. Richmon, Russell H. Taylor, Edoardo Sinibaldi, Nassir Navab:
On the reproducibility of expert-operated and robotic ultrasound acquisitions. Int. J. Comput. Assist. Radiol. Surg. 12(6): 1003-1011 (2017)
Coauthor Index
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last updated on 2025-04-14 21:10 CEST by the dblp team
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