Kayhan Batmanghelich

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 77

Top Topics

Pairwise Comparisons

Domain Adaptation

Drug Resistance

Causal Discovery

Top Venues

Medical Image Anal.

Publications

Ke Yu, Li Sun, Junxiang Chen, Maxwell Reynolds, Tigmanshu Chaudhary, Kayhan Batmanghelich
DrasCLR: A self-supervised framework of learning disease-related and anatomy-specific representation for 3D lung CT images. Medical Image Anal. 92 (2024)
Shantanu Ghosh, Clare B. Poynton, Shyam Visweswaran, Kayhan Batmanghelich
Mammo-CLIP: A Vision Language Foundation Model to Enhance Data Efficiency and Robustness in Mammography. CoRR (2024)
Yanwu Xu, Li Sun, Wei Peng, Shyam Visweswaran, Kayhan Batmanghelich
MedSyn: Text-guided Anatomy-aware Synthesis of High-Fidelity 3D CT Images. CoRR (2023)
Matthew Ragoza, Kayhan Batmanghelich
Physics-Informed Neural Networks for Tissue Elasticity Reconstruction in Magnetic Resonance Elastography. MICCAI (10) (2023)
Amir I. Mina, Jeremy U. Espino, Allison M. Bradley, Parthasarathy Thirumala, Kayhan Batmanghelich, Shyam Visweswaran
Time-Series Aware Metrics for the Evaluation of Intraoperative Electroencephalography-Based Ischemia Detection. MedInfo (2023)
Sumedha Singla, Nihal Murali, Forough Arabshahi, Sofia Triantafyllou, Kayhan Batmanghelich
Augmentation by Counterfactual Explanation -Fixing an Overconfident Classifier. WACV (2023)
Shantanu Ghosh, Ke Yu, Forough Arabshahi, Kayhan Batmanghelich
Route, Interpret, Repeat: Blurring the Line Between Post hoc Explainability and Interpretable Models. CoRR (2023)
Shantanu Ghosh, Ke Yu, Forough Arabshahi, Kayhan Batmanghelich
Dividing and Conquering a BlackBox to a Mixture of Interpretable Models: Route, Interpret, Repeat. CoRR (2023)
Yanwu Xu, Mingming Gong, Shaoan Xie, Wei Wei, Matthias Grundmann, Kayhan Batmanghelich, Tingbo Hou
Semi-Implicit Denoising Diffusion Models (SIDDMs). NeurIPS (2023)
Sumedha Singla, Motahhare Eslami, Brian Pollack, Stephen Wallace, Kayhan Batmanghelich
Explaining the black-box smoothly - A counterfactual approach. Medical Image Anal. 84 (2023)
Nihal Murali, Aahlad Manas Puli, Ke Yu, Rajesh Ranganath, Kayhan Batmanghelich
Shortcut Learning Through the Lens of Early Training Dynamics. CoRR (2023)
Shantanu Ghosh, Ke Yu, Kayhan Batmanghelich
Distilling BlackBox to Interpretable models for Efficient Transfer Learning. CoRR (2023)
Reuben Dorent, Aaron Kujawa, Marina Ivory, Spyridon Bakas, Nicola Rieke, Samuel Joutard, Ben Glocker, Jorge Cardoso, Marc Modat, Kayhan Batmanghelich, Arseniy Belkov, Maria G. Baldeon Calisto, Jae Won Choi, Benoit M. Dawant, Hexin Dong, Sergio Escalera, Yubo Fan, Lasse Hansen, Mattias P. Heinrich, Smriti Joshi, Victoriya Kashtanova, Hyeongyu Kim, Satoshi Kondo, Christian N. Kruse, Susana K. Lai-Yuen, Hao Li, Han Liu, Buntheng Ly, Ipek Oguz, Hyungseob Shin, Boris Shirokikh, Zixian Su, Guotai Wang, Jianghao Wu, Yanwu Xu, Kai Yao, Li Zhang, Sébastien Ourselin, Jonathan Shapey, Tom Vercauteren
CrossMoDA 2021 challenge: Benchmark of cross-modality domain adaptation techniques for vestibular schwannoma and cochlea segmentation. Medical Image Anal. 83 (2023)
Ke Yu, Stephen Albro, Giulia DeSalvo, Suraj Kothawade, Abdullah Rashwan, Sasan Tavakkol, Kayhan Batmanghelich, Xiaoqi Yin
Two-Step Active Learning for Instance Segmentation with Uncertainty and Diversity Sampling. CoRR (2023)
Yanwu Xu, Mingming Gong, Shaoan Xie, Wei Wei, Matthias Grundmann, Kayhan Batmanghelich, Tingbo Hou
Semi-Implicit Denoising Diffusion Models (SIDDMs). CoRR (2023)
Nihal Murali, Aahlad Manas Puli, Ke Yu, Rajesh Ranganath, Kayhan Batmanghelich
Beyond Distribution Shift: Spurious Features Through the Lens of Training Dynamics. Trans. Mach. Learn. Res. 2023 (2023)
Ke Yu, Li Sun, Junxiang Chen, Maxwell Reynolds, Tigmanshu Chaudhary, Kayhan Batmanghelich
DrasCLR: A Self-supervised Framework of Learning Disease-related and Anatomy-specific Representation for 3D Medical Images. CoRR (2023)
Li Sun, Florian Luisier, Kayhan Batmanghelich, Dinei A. F. Florêncio, Cha Zhang
From Characters to Words: Hierarchical Pre-trained Language Model for Open-vocabulary Language Understanding. ACL (1) (2023)
Li Sun, Florian Luisier, Kayhan Batmanghelich, Dinei A. F. Florêncio, Cha Zhang
From Characters to Words: Hierarchical Pre-trained Language Model for Open-vocabulary Language Understanding. CoRR (2023)
Shantanu Ghosh, Kayhan Batmanghelich
Exploring the Lottery Ticket Hypothesis with Explainability Methods: Insights into Sparse Network Performance. CoRR (2023)
Shantanu Ghosh, Ke Yu, Forough Arabshahi, Kayhan Batmanghelich
Dividing and Conquering a BlackBox to a Mixture of Interpretable Models: Route, Interpret, Repeat. ICML (2023)
Shantanu Ghosh, Ke Yu, Kayhan Batmanghelich
Distilling BlackBox to Interpretable Models for Efficient Transfer Learning. MICCAI (2) (2023)
Reuben Dorent, Aaron Kujawa, Marina Ivory, Spyridon Bakas, Nicola Rieke, Samuel Joutard, Ben Glocker, Jorge Cardoso, Marc Modat, Kayhan Batmanghelich, Arseniy Belkov, Maria G. Baldeon Calisto, Jae Won Choi, Benoit M. Dawant, Hexin Dong, Sergio Escalera, Yubo Fan, Lasse Hansen, Mattias P. Heinrich, Smriti Joshi, Victoriya Kashtanova, Hyeongyu Kim, Satoshi Kondo, Christian N. Kruse, Susana K. Lai-Yuen, Hao Li, Han Liu, Buntheng Ly, Ipek Oguz, Hyungseob Shin, Boris Shirokikh, Zixian Su, Guotai Wang, Jianghao Wu, Yanwu Xu, Kai Yao, Li Zhang, Sébastien Ourselin, Jonathan Shapey, Tom Vercauteren
CrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwnannoma and Cochlea Segmentation. CoRR (2022)
Yanwu Xu, Shaoan Xie, Maxwell Reynolds, Matthew Ragoza, Mingming Gong, Kayhan Batmanghelich
Adversarial Consistency for Single Domain Generalization in Medical Image Segmentation. CoRR (2022)
Ke Yu, Shantanu Ghosh, Zhexiong Liu, Christopher Deible, Kayhan Batmanghelich
Anatomy-Guided Weakly-Supervised Abnormality Localization in Chest X-rays. MICCAI (5) (2022)
Yanwu Xu, Shaoan Xie, Maxwell Reynolds, Matthew Ragoza, Mingming Gong, Kayhan Batmanghelich
Adversarial Consistency for Single Domain Generalization in Medical Image Segmentation. MICCAI (8) (2022)
Li Sun, Junxiang Chen, Yanwu Xu, Mingming Gong, Ke Yu, Kayhan Batmanghelich
Hierarchical Amortized GAN for 3D High Resolution Medical Image Synthesis. IEEE J. Biomed. Health Informatics 26 (8) (2022)
Li Sun, Ke Yu, Kayhan Batmanghelich
Context-aware Self-supervised Learning for Medical Images Using Graph Neural Network. CoRR (2022)
Ke Yu, Shyam Visweswaran, Kayhan Batmanghelich
Hyperbolic Molecular Representation Learning for Drug Repositioning. CoRR (2022)
Sumedha Singla, Nihal Murali, Forough Arabshahi, Sofia Triantafyllou, Kayhan Batmanghelich
Augmentation by Counterfactual Explanation - Fixing an Overconfident Classifier. CoRR (2022)
Yanwu Xu, Shaoan Xie, Wenhao Wu, Kun Zhang, Mingming Gong, Kayhan Batmanghelich
Maximum Spatial Perturbation Consistency for Unpaired Image-to-Image Translation. CVPR (2022)
Yanwu Xu, Shaoan Xie, Wenhao Wu, Kun Zhang, Mingming Gong, Kayhan Batmanghelich
Maximum Spatial Perturbation Consistency for Unpaired Image-to-Image Translation. CoRR (2022)
Ardavan Saeedi, Yuria Utsumi, Li Sun, Kayhan Batmanghelich, Li-Wei H. Lehman
Knowledge Distillation via Constrained Variational Inference. AAAI (2022)
Ke Yu, Shantanu Ghosh, Zhexiong Liu, Christopher Deible, Kayhan Batmanghelich
Anatomy-Guided Weakly-Supervised Abnormality Localization in Chest X-rays. CoRR (2022)
Rohit Jena, Sumedha Singla, Kayhan Batmanghelich
Self-supervised Vessel Enhancement Using Flow-Based Consistencies. MICCAI (2) (2021)
Junxiang Chen, Li Sun, Ke Yu, Kayhan Batmanghelich
Extracting Disease-Relevant Features with Adversarial Regularization. BIBM (2021)
Mingming Gong, Peng Liu, Frank C. Sciurba, Petar Stojanov, Dacheng Tao, George C. Tseng, Kun Zhang, Kayhan Batmanghelich
Unpaired data empowers association tests. Bioinform. 37 (6) (2021)
Li Sun, Ke Yu, Kayhan Batmanghelich
Context Matters: Graph-based Self-supervised Representation Learning for Medical Images. AAAI (2021)
Joshua Robinson, Li Sun, Ke Yu, Kayhan Batmanghelich, Stefanie Jegelka, Suvrit Sra
Can contrastive learning avoid shortcut solutions? NeurIPS (2021)
Sumedha Singla, Brian Pollack, Stephen Wallace, Kayhan Batmanghelich
Explaining the Black-box Smoothly- A Counterfactual Approach. CoRR (2021)
Sumedha Singla, Stephen Wallace, Sofia Triantafillou, Kayhan Batmanghelich
Using Causal Analysis for Conceptual Deep Learning Explanation. MICCAI (3) (2021)
Sumedha Singla, Stephen Wallace, Sofia Triantafillou, Kayhan Batmanghelich
Using Causal Analysis for Conceptual Deep Learning Explanation. CoRR (2021)
Ardavan Saeedi, Payman Yadollahpour, Sumedha Singla, Brian Pollack, William M. Wells III, Frank C. Sciurba, Kayhan Batmanghelich
Incorporating External Information in Tissue Subtyping: A Topic Modeling Approach. MLHC (2021)
Rohit Jena, Sumedha Singla, Kayhan Batmanghelich
Self-Supervised Vessel Enhancement Using Flow-Based Consistencies. CoRR (2021)
Yanwu Xu, Mingming Gong, Shaoan Xie, Kayhan Batmanghelich
Box-Adapt: Domain-Adaptive Medical Image Segmentation using Bounding BoxSupervision. CoRR (2021)
Joshua Robinson, Li Sun, Ke Yu, Kayhan Batmanghelich, Stefanie Jegelka, Suvrit Sra
Can contrastive learning avoid shortcut solutions? CoRR (2021)
Sumedha Singla, Brian Pollack, Junxiang Chen, Kayhan Batmanghelich
Explanation by Progressive Exaggeration. ICLR (2020)
Xiyu Yu, Tongliang Liu, Mingming Gong, Kun Zhang, Kayhan Batmanghelich, Dacheng Tao
Label-Noise Robust Domain Adaptation. ICML (2020)
Mahdyar Ravanbakhsh, Vadim Tschernezki, Felix Last, Tassilo Klein, Kayhan Batmanghelich, Volker Tresp, Moin Nabi
Human-Machine Collaboration for Medical Image Segmentation. ICASSP (2020)
Ke Yu, Shyam Visweswaran, Kayhan Batmanghelich
Semi-Supervised Hierarchical Drug Embedding in Hyperbolic Space. CoRR (2020)
Yanwu Xu, Mingming Gong, Junxiang Chen, Tongliang Liu, Kun Zhang, Kayhan Batmanghelich
Generative-Discriminative Complementary Learning. AAAI (2020)
Li Sun, Ke Yu, Kayhan Batmanghelich
Context Matters: Graph-based Self-supervised Representation Learning for Medical Images. CoRR (2020)
Ke Yu, Shyam Visweswaran, Kayhan Batmanghelich
Semi-supervised Hierarchical Drug Embedding in Hyperbolic Space. J. Chem. Inf. Model. 60 (12) (2020)
Junxiang Chen, Kayhan Batmanghelich
Weakly Supervised Disentanglement by Pairwise Similarities. AAAI (2020)
Li Sun, Junxiang Chen, Yanwu Xu, Mingming Gong, Ke Yu, Kayhan Batmanghelich
Hierarchical Amortized Training for Memory-efficient High Resolution 3D GAN. CoRR (2020)
Junxiang Chen, Kayhan Batmanghelich
Weakly Supervised Disentanglement by Pairwise Similarities. CoRR (2019)
Sumedha Singla, Brian Pollack, Junxiang Chen, Kayhan Batmanghelich
Explanation by Progressive Exaggeration. CoRR (2019)
Yanwu Xu, Mingming Gong, Tongliang Liu, Kayhan Batmanghelich, Chaohui Wang
Robust Angular Local Descriptor Learning. CoRR (2019)
Yipeng Mou, Mingming Gong, Huan Fu, Kayhan Batmanghelich, Kun Zhang, Dacheng Tao
Learning Depth from Monocular Videos Using Synthetic Data: A Temporally-Consistent Domain Adaptation Approach. CoRR (2019)
Junxiang Chen, Kayhan Batmanghelich
Robust Ordinal VAE: Employing Noisy Pairwise Comparisons for Disentanglement. CoRR (2019)
Yanwu Xu, Mingming Gong, Junxiang Chen, Tongliang Liu, Kun Zhang, Kayhan Batmanghelich
Generative-Discriminative Complementary Learning. CoRR (2019)
Huan Fu, Mingming Gong, Chaohui Wang, Kayhan Batmanghelich, Kun Zhang, Dacheng Tao
Geometry-Consistent Generative Adversarial Networks for One-Sided Unsupervised Domain Mapping. CVPR (2019)
Mingming Gong, Yanwu Xu, Chunyuan Li, Kun Zhang, Kayhan Batmanghelich
Twin Auxiliary Classifiers GAN. CoRR (2019)
Mingming Gong, Yanwu Xu, Chunyuan Li, Kun Zhang, Kayhan Batmanghelich
Twin Auxilary Classifiers GAN. NeurIPS (2019)
Huan Fu, Mingming Gong, Chaohui Wang, Kayhan Batmanghelich, Dacheng Tao
Deep Ordinal Regression Network for Monocular Depth Estimation. CoRR (2018)
Huan Fu, Mingming Gong, Chaohui Wang, Kayhan Batmanghelich, Kun Zhang, Dacheng Tao
Geometry-Consistent Adversarial Networks for One-Sided Unsupervised Domain Mapping. CoRR (2018)
Kun Zhang, Mingming Gong, Joseph D. Ramsey, Kayhan Batmanghelich, Peter Spirtes, Clark Glymour
Causal Discovery with Linear Non-Gaussian Models under Measurement Error: Structural Identifiability Results. UAI (2018)
Mingming Gong, Kun Zhang, Biwei Huang, Clark Glymour, Dacheng Tao, Kayhan Batmanghelich
Causal Generative Domain Adaptation Networks. CoRR (2018)
Yanwu Xu, Mingming Gong, Huan Fu, Dacheng Tao, Kun Zhang, Kayhan Batmanghelich
Multi-scale Masked 3-D U-Net for Brain Tumor Segmentation. BrainLes@MICCAI (2) (2018)
Huan Fu, Mingming Gong, Chaohui Wang, Kayhan Batmanghelich, Dacheng Tao
Deep Ordinal Regression Network for Monocular Depth Estimation. CVPR (2018)
Yanwu Xu, Mingming Gong, Tongliang Liu, Kayhan Batmanghelich, Chaohui Wang
Robust Angular Local Descriptor Learning. ACCV (5) (2018)
Xiyu Yu, Tongliang Liu, Mingming Gong, Kayhan Batmanghelich, Dacheng Tao
An Efficient and Provable Approach for Mixture Proportion Estimation Using Linear Independence Assumption. CVPR (2018)
Oren Freifeld, Søren Hauberg, Kayhan Batmanghelich, Jonn W. Fisher
Transformations Based on Continuous Piecewise-Affine Velocity Fields. IEEE Trans. Pattern Anal. Mach. Intell. 39 (12) (2017)
Yashin Dicente Cid, Kayhan Batmanghelich, Henning Müller
Textured Graph-Based Model of the Lungs: Application on Tuberculosis Type Classification and Multi-drug Resistance Detection. CLEF (2017)
Kun Zhang, Mingming Gong, Joseph D. Ramsey, Kayhan Batmanghelich, Peter Spirtes, Clark Glymour
Causal Discovery in the Presence of Measurement Error: Identifiability Conditions. CoRR (2017)
Yashin Dicente Cid, Kayhan Batmanghelich, Henning Müller
Textured Graph-model of the Lungs for Tuberculosis Type Classification and Drug Resistance Prediction: Participation in ImageCLEF 2017. CLEF (Working Notes) (2017)
Yashin Dicente Cid, Henning Müller, Kayhan Batmanghelich
BatmanLab in the ImageCLEF Tuberculosis task 2017. CLEF (Working Notes) (2017)