Batmanghelich, Kayhan

18 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
NeurIPS 2019 Twin Auxilary Classifiers GAN Mingming Gong, Yanwu Xu, Chunyuan Li, Kun Zhang, Kayhan Batmanghelich
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
ICCV 2015 Highly-Expressive Spaces of Well-Behaved Transformations: Keeping It Simple Oren Freifeld, Soren Hauberg, Kayhan Batmanghelich, John W. Fisher Iii