Batmanghelich, Kayhan

21 publications

WACV 2025 Multi-Modal Large Language Models Are Effective Vision Learners Li Sun, Chaitanya Ahuja, Peng Chen, Matt D'Zmura, Kayhan Batmanghelich, Philip Bontrager

WACV 2023 Augmentation by Counterfactual Explanation - Fixing an Overconfident Classifier Sumedha Singla, Nihal Murali, Forough Arabshahi, Sofia Triantafyllou, Kayhan Batmanghelich

TMLR 2023 Beyond Distribution Shift: Spurious Features Through the Lens of Training Dynamics Nihal Murali, Aahlad Manas Puli, Ke Yu, Rajesh Ranganath, Kayhan Batmanghelich

ICMLW 2023 Bridging the Gap: From Post Hoc Explanations to Inherently Interpretable Models for Medical Imaging Shantanu Ghosh, Ke Yu, Forough Arabshahi, Kayhan Batmanghelich

ICML 2023 Dividing and Conquering a BlackBox to a Mixture of Interpretable Models: Route, Interpret, Repeat Shantanu Ghosh, Ke Yu, Forough Arabshahi, Kayhan Batmanghelich

NeurIPS 2023 Semi-Implicit Denoising Diffusion Models (SIDDMs) Yanwu Xu, Mingming Gong, Shaoan Xie, Wei Wei, Matthias Grundmann, Kayhan Batmanghelich, Tingbo Hou

AAAI 2022 Knowledge Distillation via Constrained Variational Inference Ardavan Saeedi, Yuria Utsumi, Li Sun, Kayhan Batmanghelich, Li-Wei H. Lehman

CVPR 2022 Maximum Spatial Perturbation Consistency for Unpaired Image-to-Image Translation Yanwu Xu, Shaoan Xie, Wenhao Wu, Kun Zhang, Mingming Gong, Kayhan Batmanghelich

NeurIPS 2021 Can Contrastive Learning Avoid Shortcut Solutions? Joshua W. Robinson, Li Sun, Ke Yu, Kayhan Batmanghelich, Stefanie Jegelka, Suvrit Sra

AAAI 2021 Context Matters: Graph-Based Self-Supervised Representation Learning for Medical Images Li Sun, Ke Yu, Kayhan Batmanghelich

MLHC 2021 Incorporating External Information in Tissue Subtyping: A Topic Modeling Approach Ardvan Saeedi, Payman Yadollahpour, Sumedha Singla, Brian Pollack, William Wells, Frank Sciurba, Kayhan Batmanghelich

ICLR 2020 Explanation by Progressive Exaggeration Sumedha Singla, Brian Pollack, Junxiang Chen, Kayhan Batmanghelich

AAAI 2020 Generative-Discriminative Complementary Learning Yanwu Xu, Mingming Gong, Junxiang Chen, Tongliang Liu, Kun Zhang, Kayhan Batmanghelich

ICML 2020 Label-Noise Robust Domain Adaptation Xiyu Yu, Tongliang Liu, Mingming Gong, Kun Zhang, Kayhan Batmanghelich, Dacheng Tao

AAAI 2020 Weakly Supervised Disentanglement by Pairwise Similarities Junxiang Chen, Kayhan Batmanghelich

CVPR 2019 Geometry-Consistent Generative Adversarial Networks for One-Sided Unsupervised Domain Mapping Huan Fu, Mingming Gong, Chaohui Wang, Kayhan Batmanghelich, Kun Zhang, Dacheng Tao

NeurIPS 2019 Twin Auxilary Classifiers GAN Mingming Gong, Yanwu Xu, Chunyuan Li, Kun Zhang, Kayhan Batmanghelich

CVPR 2018 An Efficient and Provable Approach for Mixture Proportion Estimation Using Linear Independence Assumption Xiyu Yu, Tongliang Liu, Mingming Gong, Kayhan Batmanghelich, Dacheng Tao

UAI 2018 Causal Discovery with Linear Non-Gaussian Models Under Measurement Error: Structural Identifiability Results Kun Zhang, Mingming Gong, Joseph D. Ramsey, Kayhan Batmanghelich, Peter Spirtes, Clark Glymour

CVPR 2018 Deep Ordinal Regression Network for Monocular Depth Estimation Huan Fu, Mingming Gong, Chaohui Wang, Kayhan Batmanghelich, Dacheng Tao

ICCV 2015 Highly-Expressive Spaces of Well-Behaved Transformations: Keeping It Simple Oren Freifeld, Soren Hauberg, Kayhan Batmanghelich, John W. Fisher Iii