Balaji, Yogesh

22 publications

ICLR 2026 InfoTok: Adaptive Discrete Video Tokenizer via Information-Theoretic Compression Haotian Ye, Qiyuan He, Jiaqi Han, Puheng Li, Jiaojiao Fan, Zekun Hao, Fitsum Reda, Yogesh Balaji, Huayu Chen, Sheng Liu, Angela Yao, James Zou, Stefano Ermon, Haoxiang Wang, Ming-Yu Liu

ICLR 2026 Large Scale Diffusion Distillation via Score-Regularized Continuous-Time Consistency Kaiwen Zheng, Yuji Wang, Qianli Ma, Huayu Chen, Jintao Zhang, Yogesh Balaji, Jianfei Chen, Ming-Yu Liu, Jun Zhu, Qinsheng Zhang

CVPR 2025 A Comprehensive Study of Decoder-Only LLMs for Text-to-Image Generation Andrew Z. Wang, Songwei Ge, Tero Karras, Ming-Yu Liu, Yogesh Balaji

ICML 2025 One-Step Diffusion Policy: Fast Visuomotor Policies via Diffusion Distillation Zhendong Wang, Max Li, Ajay Mandlekar, Zhenjia Xu, Jiaojiao Fan, Yashraj Narang, Linxi Fan, Yuke Zhu, Yogesh Balaji, Mingyuan Zhou, Ming-Yu Liu, Yu Zeng

CVPR 2024 JeDi: Joint-Image Diffusion Models for Finetuning-Free Personalized Text-to-Image Generation Yu Zeng, Vishal M. Patel, Haochen Wang, Xun Huang, Ting-Chun Wang, Ming-Yu Liu, Yogesh Balaji

ICCV 2023 Preserve Your Own Correlation: A Noise Prior for Video Diffusion Models Songwei Ge, Seungjun Nah, Guilin Liu, Tyler Poon, Andrew Tao, Bryan Catanzaro, David Jacobs, Jia-Bin Huang, Ming-Yu Liu, Yogesh Balaji

CVPR 2022 A Comprehensive Study of Image Classification Model Sensitivity to Foregrounds, Backgrounds, and Visual Attributes Mazda Moayeri, Phillip Pope, Yogesh Balaji, Soheil Feizi

ICLR 2021 Understanding Over-Parameterization in Generative Adversarial Networks Yogesh Balaji, Mohammadmahdi Sajedi, Neha Mukund Kalibhat, Mucong Ding, Dominik Stöger, Mahdi Soltanolkotabi, Soheil Feizi

UAI 2021 Unsupervised Anomaly Detection with Adversarial Mirrored Autoencoders Gowthami Somepalli, Yexin Wu, Yogesh Balaji, Bhanukiran Vinzamuri, Soheil Feizi

AAAI 2021 Winning Lottery Tickets in Deep Generative Models Neha Mukund Kalibhat, Yogesh Balaji, Soheil Feizi

AISTATS 2020 Adversarial Robustness of Flow-Based Generative Models Phillip Pope, Yogesh Balaji, Soheil Feizi

ECCV 2020 Curriculum Manager for Source Selection in Multi-Source Domain Adaptation Luyu Yang, Yogesh Balaji, Ser-Nam Lim, Abhinav Shrivastava

ECCV 2020 Learning to Balance Specificity and Invariance for in and Out of Domain Generalization Prithvijit Chattopadhyay, Yogesh Balaji, Judy Hoffman

NeurIPS 2020 Robust Optimal Transport with Applications in Generative Modeling and Domain Adaptation Yogesh Balaji, Rama Chellappa, Soheil Feizi

IJCAI 2019 Conditional GAN with Discriminative Filter Generation for Text-to-Video Synthesis Yogesh Balaji, Martin Renqiang Min, Bing Bai, Rama Chellappa, Hans Peter Graf

ICML 2019 Entropic GANs Meet VAEs: A Statistical Approach to Compute Sample Likelihoods in GANs Yogesh Balaji, Hamed Hassani, Rama Chellappa, Soheil Feizi

ICCV 2019 Normalized Wasserstein for Mixture Distributions with Applications in Adversarial Learning and Domain Adaptation Yogesh Balaji, Rama Chellappa, Soheil Feizi

CVPR 2018 Generate to Adapt: Aligning Domains Using Generative Adversarial Networks Swami Sankaranarayanan, Yogesh Balaji, Carlos D. Castillo, Rama Chellappa

CVPR 2018 Learning from Synthetic Data: Addressing Domain Shift for Semantic Segmentation Swami Sankaranarayanan, Yogesh Balaji, Arpit Jain, Ser Nam Lim, Rama Chellappa

NeurIPS 2018 MetaReg: Towards Domain Generalization Using Meta-Regularization Yogesh Balaji, Swami Sankaranarayanan, Rama Chellappa

CVPR 2017 Unrolling the Shutter: CNN to Correct Motion Distortions Vijay Rengarajan, Yogesh Balaji, A. N. Rajagopalan

ECCV 2016 Deep Decoupling of Defocus and Motion Blur for Dynamic Segmentation Abhijith Punnappurath, Yogesh Balaji, Mahesh Mohan M. R., Ambasamudram Narayanan Rajagopalan