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Kayhan Batmanghelich
Person information
- affiliation: University of Pittsburgh, Department of Biomedical Informatics, PA, USA
- affiliation (former): Massachusetts Institute of Technology (MIT), Computer Science and Artificial Intelligence Lab
- affiliation (former): University of Pennsylvania, Section of Biomedical Image Analysis
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2020 – today
- 2024
- [j12]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: 103062 (2024) - [c51]Shantanu Ghosh, Clare B. Poynton, Shyam Visweswaran, Kayhan Batmanghelich:
Mammo-CLIP: A Vision Language Foundation Model to Enhance Data Efficiency and Robustness in Mammography. MICCAI (12) 2024: 632-642 - [i43]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 abs/2405.12255 (2024) - [i42]Shantanu Ghosh, Chenyu Wang, Kayhan Batmanghelich:
LADDER: Language Driven Slice Discovery and Error Rectification. CoRR abs/2408.07832 (2024) - 2023
- [j11]Reuben Dorent, Aaron Kujawa, Marina Ivory, Spyridon Bakas, Nicola Rieke, Samuel Joutard, Ben Glocker, M. 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: 102628 (2023) - [j10]Sumedha Singla, Motahhare Eslami, Brian Pollack, Stephen Wallace, Kayhan Batmanghelich:
Explaining the black-box smoothly - A counterfactual approach. Medical Image Anal. 84: 102721 (2023) - [j9]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) - [c50]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: 3605-3620 - [c49]Shantanu Ghosh, Ke Yu, Forough Arabshahi, Kayhan Batmanghelich:
Dividing and Conquering a BlackBox to a Mixture of Interpretable Models: Route, Interpret, Repeat. ICML 2023: 11360-11397 - [c48]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: 274-278 - [c47]Matthew Ragoza, Kayhan Batmanghelich:
Physics-Informed Neural Networks for Tissue Elasticity Reconstruction in Magnetic Resonance Elastography. MICCAI (10) 2023: 333-343 - [c46]Shantanu Ghosh, Ke Yu, Kayhan Batmanghelich:
Distilling BlackBox to Interpretable Models for Efficient Transfer Learning. MICCAI (2) 2023: 628-638 - [c45]Yanwu Xu, Mingming Gong, Shaoan Xie, Wei Wei, Matthias Grundmann, Kayhan Batmanghelich, Tingbo Hou:
Semi-Implicit Denoising Diffusion Models (SIDDMs). NeurIPS 2023 - [c44]Sumedha Singla, Nihal Murali, Forough Arabshahi, Sofia Triantafyllou, Kayhan Batmanghelich:
Augmentation by Counterfactual Explanation -Fixing an Overconfident Classifier. WACV 2023: 4709-4719 - [i41]Nihal Murali, Aahlad Manas Puli, Ke Yu, Rajesh Ranganath, Kayhan Batmanghelich:
Shortcut Learning Through the Lens of Early Training Dynamics. CoRR abs/2302.09344 (2023) - [i40]Shantanu Ghosh, Ke Yu, Forough Arabshahi, Kayhan Batmanghelich:
Route, Interpret, Repeat: Blurring the Line Between Post hoc Explainability and Interpretable Models. CoRR abs/2302.10289 (2023) - [i39]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 abs/2302.10390 (2023) - [i38]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 abs/2305.14571 (2023) - [i37]Shantanu Ghosh, Ke Yu, Kayhan Batmanghelich:
Distilling BlackBox to Interpretable models for Efficient Transfer Learning. CoRR abs/2305.17303 (2023) - [i36]Yanwu Xu, Mingming Gong, Shaoan Xie, Wei Wei, Matthias Grundmann, Kayhan Batmanghelich, Tingbo Hou:
Semi-Implicit Denoising Diffusion Models (SIDDMs). CoRR abs/2306.12511 (2023) - [i35]Shantanu Ghosh, Ke Yu, Forough Arabshahi, Kayhan Batmanghelich:
Dividing and Conquering a BlackBox to a Mixture of Interpretable Models: Route, Interpret, Repeat. CoRR abs/2307.05350 (2023) - [i34]Shantanu Ghosh, Kayhan Batmanghelich:
Exploring the Lottery Ticket Hypothesis with Explainability Methods: Insights into Sparse Network Performance. CoRR abs/2307.13698 (2023) - [i33]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 abs/2309.16139 (2023) - [i32]Yanwu Xu, Li Sun, Wei Peng, Shyam Visweswaran, Kayhan Batmanghelich:
MedSyn: Text-guided Anatomy-aware Synthesis of High-Fidelity 3D CT Images. CoRR abs/2310.03559 (2023) - 2022
- [j8]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): 3966-3975 (2022) - [c43]Ardavan Saeedi, Yuria Utsumi, Li Sun, Kayhan Batmanghelich, Li-Wei H. Lehman:
Knowledge Distillation via Constrained Variational Inference. AAAI 2022: 8132-8140 - [c42]Yanwu Xu, Shaoan Xie, Wenhao Wu, Kun Zhang, Mingming Gong, Kayhan Batmanghelich:
Maximum Spatial Perturbation Consistency for Unpaired Image-to-Image Translation. CVPR 2022: 18290-18299 - [c41]Ke Yu, Shantanu Ghosh, Zhexiong Liu, Christopher Deible, Kayhan Batmanghelich:
Anatomy-Guided Weakly-Supervised Abnormality Localization in Chest X-rays. MICCAI (5) 2022: 658-668 - [c40]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: 671-681 - [i31]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 abs/2201.02831 (2022) - [i30]Yanwu Xu, Shaoan Xie, Wenhao Wu, Kun Zhang, Mingming Gong, Kayhan Batmanghelich:
Maximum Spatial Perturbation Consistency for Unpaired Image-to-Image Translation. CoRR abs/2203.12707 (2022) - [i29]Ke Yu, Shantanu Ghosh, Zhexiong Liu, Christopher Deible, Kayhan Batmanghelich:
Anatomy-Guided Weakly-Supervised Abnormality Localization in Chest X-rays. CoRR abs/2206.12704 (2022) - [i28]Yanwu Xu, Shaoan Xie, Maxwell Reynolds, Matthew Ragoza, Mingming Gong, Kayhan Batmanghelich:
Adversarial Consistency for Single Domain Generalization in Medical Image Segmentation. CoRR abs/2206.13737 (2022) - [i27]Li Sun, Ke Yu, Kayhan Batmanghelich:
Context-aware Self-supervised Learning for Medical Images Using Graph Neural Network. CoRR abs/2207.02957 (2022) - [i26]Ke Yu, Shyam Visweswaran, Kayhan Batmanghelich:
Hyperbolic Molecular Representation Learning for Drug Repositioning. CoRR abs/2208.06361 (2022) - [i25]Sumedha Singla, Nihal Murali, Forough Arabshahi, Sofia Triantafyllou, Kayhan Batmanghelich:
Augmentation by Counterfactual Explanation - Fixing an Overconfident Classifier. CoRR abs/2210.12196 (2022) - 2021
- [j7]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): 785-792 (2021) - [c39]Li Sun, Ke Yu, Kayhan Batmanghelich:
Context Matters: Graph-based Self-supervised Representation Learning for Medical Images. AAAI 2021: 4874-4882 - [c38]Junxiang Chen, Li Sun, Ke Yu, Kayhan Batmanghelich:
Extracting Disease-Relevant Features with Adversarial Regularization. BIBM 2021: 3464-3471 - [c37]Rohit Jena, Sumedha Singla, Kayhan Batmanghelich:
Self-supervised Vessel Enhancement Using Flow-Based Consistencies. MICCAI (2) 2021: 242-251 - [c36]Sumedha Singla, Stephen Wallace, Sofia Triantafillou, Kayhan Batmanghelich:
Using Causal Analysis for Conceptual Deep Learning Explanation. MICCAI (3) 2021: 519-528 - [c35]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: 478-505 - [c34]Joshua Robinson, Li Sun, Ke Yu, Kayhan Batmanghelich, Stefanie Jegelka, Suvrit Sra:
Can contrastive learning avoid shortcut solutions? NeurIPS 2021: 4974-4986 - [i24]Sumedha Singla, Brian Pollack, Stephen Wallace, Kayhan Batmanghelich:
Explaining the Black-box Smoothly- A Counterfactual Approach. CoRR abs/2101.04230 (2021) - [i23]Rohit Jena, Sumedha Singla, Kayhan Batmanghelich:
Self-Supervised Vessel Enhancement Using Flow-Based Consistencies. CoRR abs/2101.05145 (2021) - [i22]Joshua Robinson, Li Sun, Ke Yu, Kayhan Batmanghelich, Stefanie Jegelka, Suvrit Sra:
Can contrastive learning avoid shortcut solutions? CoRR abs/2106.11230 (2021) - [i21]Sumedha Singla, Stephen Wallace, Sofia Triantafillou, Kayhan Batmanghelich:
Using Causal Analysis for Conceptual Deep Learning Explanation. CoRR abs/2107.06098 (2021) - [i20]Yanwu Xu, Mingming Gong, Shaoan Xie, Kayhan Batmanghelich:
Box-Adapt: Domain-Adaptive Medical Image Segmentation using Bounding BoxSupervision. CoRR abs/2108.08432 (2021) - 2020
- [j6]Ke Yu, Shyam Visweswaran, Kayhan Batmanghelich:
Semi-supervised Hierarchical Drug Embedding in Hyperbolic Space. J. Chem. Inf. Model. 60(12): 5647-5657 (2020) - [c33]Junxiang Chen, Kayhan Batmanghelich:
Weakly Supervised Disentanglement by Pairwise Similarities. AAAI 2020: 3495-3502 - [c32]Yanwu Xu, Mingming Gong, Junxiang Chen, Tongliang Liu, Kun Zhang, Kayhan Batmanghelich:
Generative-Discriminative Complementary Learning. AAAI 2020: 6526-6533 - [c31]Mahdyar Ravanbakhsh, Vadim Tschernezki, Felix Last, Tassilo Klein, Kayhan Batmanghelich, Volker Tresp, Moin Nabi:
Human-Machine Collaboration for Medical Image Segmentation. ICASSP 2020: 1040-1044 - [c30]Sumedha Singla, Brian Pollack, Junxiang Chen, Kayhan Batmanghelich:
Explanation by Progressive Exaggeration. ICLR 2020 - [c29]Xiyu Yu, Tongliang Liu, Mingming Gong, Kun Zhang, Kayhan Batmanghelich, Dacheng Tao:
Label-Noise Robust Domain Adaptation. ICML 2020: 10913-10924 - [i19]Ke Yu, Shyam Visweswaran, Kayhan Batmanghelich:
Semi-Supervised Hierarchical Drug Embedding in Hyperbolic Space. CoRR abs/2006.00986 (2020) - [i18]Li Sun, Junxiang Chen, Yanwu Xu, Mingming Gong, Ke Yu, Kayhan Batmanghelich:
Hierarchical Amortized Training for Memory-efficient High Resolution 3D GAN. CoRR abs/2008.01910 (2020) - [i17]Li Sun, Ke Yu, Kayhan Batmanghelich:
Context Matters: Graph-based Self-supervised Representation Learning for Medical Images. CoRR abs/2012.06457 (2020)
2010 – 2019
- 2019
- [c28]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: 2427-2436 - [c27]Mingming Gong, Yanwu Xu, Chunyuan Li, Kun Zhang, Kayhan Batmanghelich:
Twin Auxilary Classifiers GAN. NeurIPS 2019: 1328-1337 - [i16]Yanwu Xu, Mingming Gong, Tongliang Liu, Kayhan Batmanghelich, Chaohui Wang:
Robust Angular Local Descriptor Learning. CoRR abs/1901.07076 (2019) - [i15]Yanwu Xu, Mingming Gong, Junxiang Chen, Tongliang Liu, Kun Zhang, Kayhan Batmanghelich:
Generative-Discriminative Complementary Learning. CoRR abs/1904.01612 (2019) - [i14]Junxiang Chen, Kayhan Batmanghelich:
Weakly Supervised Disentanglement by Pairwise Similarities. CoRR abs/1906.01044 (2019) - [i13]Mingming Gong, Yanwu Xu, Chunyuan Li, Kun Zhang, Kayhan Batmanghelich:
Twin Auxiliary Classifiers GAN. CoRR abs/1907.02690 (2019) - [i12]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 abs/1907.06882 (2019) - [i11]Junxiang Chen, Kayhan Batmanghelich:
Robust Ordinal VAE: Employing Noisy Pairwise Comparisons for Disentanglement. CoRR abs/1910.05898 (2019) - [i10]Sumedha Singla, Brian Pollack, Junxiang Chen, Kayhan Batmanghelich:
Explanation by Progressive Exaggeration. CoRR abs/1911.00483 (2019) - 2018
- [j5]Sjoerd M. H. Huisman, Ahmed Mahfouz, Nematollah Kayhan Batmanghelich, Boudewijn P. F. Lelieveldt, Marcel J. T. Reinders:
A structural equation model for imaging genetics using spatial transcriptomics. Brain Informatics 5(2) (2018) - [c26]Yanwu Xu, Mingming Gong, Tongliang Liu, Kayhan Batmanghelich, Chaohui Wang:
Robust Angular Local Descriptor Learning. ACCV (5) 2018: 420-435 - [c25]Huan Fu, Mingming Gong, Chaohui Wang, Kayhan Batmanghelich, Dacheng Tao:
Deep Ordinal Regression Network for Monocular Depth Estimation. CVPR 2018: 2002-2011 - [c24]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: 4480-4489 - [c23]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: 222-233 - [c22]Sumedha Singla, Mingming Gong, Siamak Ravanbakhsh, Frank C. Sciurba, Barnabás Póczos, Kayhan N. Batmanghelich:
Subject2Vec: Generative-Discriminative Approach from a Set of Image Patches to a Vector. MICCAI (1) 2018: 502-510 - [c21]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: 1063-1072 - [i9]Mingming Gong, Kun Zhang, Biwei Huang, Clark Glymour, Dacheng Tao, Kayhan Batmanghelich:
Causal Generative Domain Adaptation Networks. CoRR abs/1804.04333 (2018) - [i8]Huan Fu, Mingming Gong, Chaohui Wang, Kayhan Batmanghelich, Dacheng Tao:
Deep Ordinal Regression Network for Monocular Depth Estimation. CoRR abs/1806.02446 (2018) - [i7]Sumedha Singla, Mingming Gong, Siamak Ravanbakhsh, Frank C. Sciurba, Barnabás Póczos, Kayhan N. Batmanghelich:
Subject2Vec: Generative-Discriminative Approach from a Set of Image Patches to a Vector. CoRR abs/1806.11217 (2018) - [i6]Huan Fu, Mingming Gong, Chaohui Wang, Kayhan Batmanghelich, Kun Zhang, Dacheng Tao:
Geometry-Consistent Adversarial Networks for One-Sided Unsupervised Domain Mapping. CoRR abs/1809.05852 (2018) - [i5]Hadi Salman, Payman Yadollahpour, Tom Fletcher, Kayhan N. Batmanghelich:
Deep Diffeomorphic Normalizing Flows. CoRR abs/1810.03256 (2018) - [i4]Spyridon Bakas, Mauricio Reyes, András Jakab, Stefan Bauer, Markus Rempfler, Alessandro Crimi, Russell Takeshi Shinohara, Christoph Berger, Sung Min Ha, Martin Rozycki, Marcel Prastawa, Esther Alberts, Jana Lipková, John B. Freymann, Justin S. Kirby, Michel Bilello, Hassan M. Fathallah-Shaykh, Roland Wiest, Jan Kirschke, Benedikt Wiestler, Rivka R. Colen, Aikaterini Kotrotsou, Pamela LaMontagne, Daniel S. Marcus, Mikhail Milchenko, Arash Nazeri, Marc-André Weber, Abhishek Mahajan, Ujjwal Baid, Dongjin Kwon, Manu Agarwal, Mahbubul Alam, Alberto Albiol, Antonio Albiol, Alex Varghese, Tran Anh Tuan, Tal Arbel, Aaron Avery, Pranjal B., Subhashis Banerjee, Thomas Batchelder, Kayhan N. Batmanghelich, Enzo Battistella, Martin Bendszus, Eze Benson, José Bernal, George Biros, Mariano Cabezas, Siddhartha Chandra, Yi-Ju Chang, et al.:
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge. CoRR abs/1811.02629 (2018) - 2017
- [j4]Oren Freifeld, Søren Hauberg, Kayhan Batmanghelich, John W. Fisher III:
Transformations Based on Continuous Piecewise-Affine Velocity Fields. IEEE Trans. Pattern Anal. Mach. Intell. 39(12): 2496-2509 (2017) - [c20]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 - [c19]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: 157-168 - [c18]Yashin Dicente Cid, Henning Müller, Kayhan Batmanghelich:
BatmanLab in the ImageCLEF Tuberculosis task 2017. CLEF (Working Notes) 2017 - [c17]Jenna Schabdach, William M. Wells III, Michael H. Cho, Kayhan N. Batmanghelich:
A Likelihood-Free Approach for Characterizing Heterogeneous Diseases in Large-Scale Studies. IPMI 2017: 170-183 - [e1]M. Jorge Cardoso, Tal Arbel, Enzo Ferrante, Xavier Pennec, Adrian V. Dalca, Sarah Parisot, Sarang C. Joshi, Nematollah Kayhan Batmanghelich, Aristeidis Sotiras, Mads Nielsen, Mert R. Sabuncu, Tom Fletcher, Li Shen, Stanley Durrleman, Stefan Sommer:
Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics - First International Workshop, GRAIL 2017, 6th International Workshop, MFCA 2017, and Third International Workshop, MICGen 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 10-14, 2017, Proceedings. Lecture Notes in Computer Science 10551, Springer 2017, ISBN 978-3-319-67674-6 [contents] - [i3]Kun Zhang, Mingming Gong, Joseph D. Ramsey, Kayhan Batmanghelich, Peter Spirtes, Clark Glymour:
Causal Discovery in the Presence of Measurement Error: Identifiability Conditions. CoRR abs/1706.03768 (2017) - 2016
- [c16]Kayhan N. Batmanghelich, Ardavan Saeedi, Karthik Narasimhan, Samuel Gershman:
Nonparametric Spherical Topic Modeling with Word Embeddings. ACL (2) 2016 - [c15]Nematollah Kayhan Batmanghelich, Ardavan Saeedi, Raúl San José Estépar, Michael H. Cho, William M. Wells III:
Inferring Disease Status by Non-parametric Probabilistic Embedding. MCV/BAMBI@MICCAI 2016: 49-57 - [c14]Polina Binder, Nematollah Kayhan Batmanghelich, Raúl San José Estépar, Polina Golland:
Unsupervised Discovery of Emphysema Subtypes in a Large Clinical Cohort. MLMI@MICCAI 2016: 180-187 - [i2]Kayhan N. Batmanghelich, Ardavan Saeedi, Karthik Narasimhan, Samuel Gershman:
Nonparametric Spherical Topic Modeling with Word Embeddings. CoRR abs/1604.00126 (2016) - 2015
- [c13]Oren Freifeld, Søren Hauberg, Kayhan N. Batmanghelich, John W. Fisher III:
Highly-Expressive Spaces of Well-Behaved Transformations: Keeping it Simple. ICCV 2015: 2911-2919 - [c12]Nematollah Kayhan Batmanghelich, Ardavan Saeedi, Michael H. Cho, Raúl San José Estépar, Polina Golland:
Generative Method to Discover Genetically Driven Image Biomarkers. IPMI 2015: 30-42 - 2014
- [c11]Kayhan N. Batmanghelich, Michael H. Cho, Raúl San José Estépar, Polina Golland:
Spherical Topic Models for Imaging Phenotype Discovery in Genetic Studies. BAMBI 2014: 107-117 - [i1]Nematollah Kayhan Batmanghelich, Gerald T. Quon, Alex Kulesza, Manolis Kellis, Polina Golland, Luke Bornn:
Diversifying Sparsity Using Variational Determinantal Point Processes. CoRR abs/1411.6307 (2014) - 2013
- [c10]Nematollah Batmanghelich, Adrian V. Dalca, Mert R. Sabuncu, Polina Golland:
Joint Modeling of Imaging and Genetics. IPMI 2013: 766-777 - 2012
- [j3]Luke Bloy, Madhura Ingalhalikar, Nematollah Batmanghelich, Robert T. Schultz, Timothy P. L. Roberts, Ragini Verma:
An Integrated Framework for High Angular Resolution Diffusion Imaging-Based Investigation of Structural Connectivity. Brain Connect. 2(2): 69-79 (2012) - [j2]Nematollah Batmanghelich, Ben Taskar, Christos Davatzikos:
Generative-Discriminative Basis Learning for Medical Imaging. IEEE Trans. Medical Imaging 31(1): 51-69 (2012) - [c9]Yasser Ghanbari, Luke Bloy, Kayhan N. Batmanghelich, Timothy P. L. Roberts, Ragini Verma:
Dominant Component Analysis of Electrophysiological Connectivity Networks. MICCAI (3) 2012: 231-238 - 2011
- [c8]Kayhan N. Batmanghelich, Dong Hye Ye, Kilian M. Pohl, Ben Taskar, Christos Davatzikos:
Disease classification and prediction via semi-supervised dimensionality reduction. ISBI 2011: 1086-1090 - [c7]Nematollah Batmanghelich, Aoyan Dong, Ben Taskar, Christos Davatzikos:
Regularized Tensor Factorization for Multi-Modality Medical Image Classification. MICCAI (3) 2011: 17-24 - 2010
- [c6]Nematollah Batmanghelich, Ali Gooya, Stathis Kanterakis, Ben Taskar, Christos Davatzikos:
Application of trace-norm and low-rank matrix decomposition for computational anatomy. CVPR Workshops 2010: 146-153
2000 – 2009
- 2009
- [c5]Nematollah Batmanghelich, Ben Taskar, Christos Davatzikos:
A General and Unifying Framework for Feature Construction, in Image-Based Pattern Classification. IPMI 2009: 423-434 - 2008
- [j1]Yong Fan, Nematollah Batmanghelich, Christopher M. Clark, Christos Davatzikos, Alzheimer's Disease Neuroimaging Initiative:
Spatial patterns of brain atrophy in MCI patients, identified via high-dimensional pattern classification, predict subsequent cognitive decline. NeuroImage 39(4): 1731-1743 (2008) - [c4]Nematollah Batmanghelich, Ragini Verma:
On non-linear characterization of tissue abnormality by constructing disease manifolds. CVPR Workshops 2008: 1-8 - [c3]Kayhan N. Batmanghelich, Xiaoying Wu, Evangelia I. Zacharaki, Clyde E. Markowitz, Christos Davatzikos, Ragini Verma:
Multiparametric tissue abnormality characterization using manifold regularization. Medical Imaging: Computer-Aided Diagnosis 2008: 691516 - 2006
- [c2]Hadi Fatemi Shariatpanahi, Nematollah Batmanghelich, Amir R. M. Kermani, Majid Nili Ahmadabadi, Hamid Soltanian-Zadeh:
Distributed Behavior-based Multi-agent System for Automatic Segmentation of Brain MR Images. IJCNN 2006: 4535-4542 - 2005
- [c1]Nematollah Batmanghelich, Hamid Soltanian-Zadeh, Babak Nadjar Araabi:
Knowledge-based segmentation: Using simultaneous shape and histogram information to segment brain structures. SIP 2005: 415-419
Coauthor Index
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last updated on 2024-11-07 20:32 CET by the dblp team
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