| 2025 | CVPR | A Comprehensive Study of Decoder-Only LLMs for Text-to-Image Generation. | Andrew Z. Wang, Songwei Ge, Tero Karras, Ming-Yu Liu, Yogesh Balaji |
| 2025 | ICML | 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 |
| 2024 | CVPR | 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 |
| 2023 | ICCV | 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 |
| 2022 | CVPR | A Comprehensive Study of Image Classification Model Sensitivity to Foregrounds, Backgrounds, and Visual Attributes. | Mazda Moayeri, Phillip Pope, Yogesh Balaji, Soheil Feizi |
| 2021 | AAAI | Winning Lottery Tickets in Deep Generative Models. | Neha Mukund Kalibhat, Yogesh Balaji, Soheil Feizi |
| 2021 | ICLR | Understanding Over-parameterization in Generative Adversarial Networks. | Yogesh Balaji, Mohammadmahdi Sajedi, Neha Mukund Kalibhat, Mucong Ding, Dominik Stger, Mahdi Soltanolkotabi, Soheil Feizi |
| 2021 | UAI | Unsupervised anomaly detection with adversarial mirrored autoencoders. | Gowthami Somepalli, Yexin Wu, Yogesh Balaji, Bhanukiran Vinzamuri, Soheil Feizi |
| 2020 | AISTATS | Adversarial Robustness of Flow-Based Generative Models. | Phillip Pope, Yogesh Balaji, Soheil Feizi |
| 2020 | ECCV | Learning to Balance Specificity and Invariance for In and Out of Domain Generalization. | Prithvijit Chattopadhyay, Yogesh Balaji, Judy Hoffman |
| 2020 | ECCV | Curriculum Manager for Source Selection in Multi-source Domain Adaptation. | Luyu Yang, Yogesh Balaji, Ser-Nam Lim, Abhinav Shrivastava |
| 2019 | ICCV | Normalized Wasserstein for Mixture Distributions With Applications in Adversarial Learning and Domain Adaptation. | Yogesh Balaji, Rama Chellappa, Soheil Feizi |
| 2019 | ICML | Entropic GANs meet VAEs: A Statistical Approach to Compute Sample Likelihoods in GANs. | Yogesh Balaji, Hamed Hassani, Rama Chellappa, Soheil Feizi |
| 2019 | IJCAI | Conditional GAN with Discriminative Filter Generation for Text-to-Video Synthesis. | Yogesh Balaji, Martin Renqiang Min, Bing Bai, Rama Chellappa, Hans Peter Graf |
| 2018 | CVPR | Learning From Synthetic Data: Addressing Domain Shift for Semantic Segmentation. | Swami Sankaranarayanan, Yogesh Balaji, Arpit Jain, Ser Nam Lim, Rama Chellappa |
| 2018 | CVPR | Generate to Adapt: Aligning Domains Using Generative Adversarial Networks. | Swami Sankaranarayanan, Yogesh Balaji, Carlos Domingo Castillo, Rama Chellappa |
| 2017 | CVPR | Unrolling the Shutter: CNN to Correct Motion Distortions. | Vijay Rengarajan, Yogesh Balaji, A. N. Rajagopalan |
| 2016 | ECCV | Deep Decoupling of Defocus and Motion Blur for Dynamic Segmentation. | Abhijith Punnappurath, Yogesh Balaji, Mahesh Mohan M. R., Ambasamudram Narayanan Rajagopalan |