Deep Decoupling of Defocus and Motion Blur for Dynamic Segmentation. - Abhijith Punnappurath; Yogesh Balaji; Mahesh Mohan M. R.; Ambasamudram Narayanan Rajagopalan (ECCV (7), 2016)

Unrolling the Shutter: CNN to Correct Motion Distortions. - Vijay Rengarajan; Yogesh Balaji; A. N. Rajagopalan 001 (CVPR, 2017)

Unsupervised Domain Adaptation for Semantic Segmentation with GANs. - Swami Sankaranarayanan; Yogesh Balaji; Arpit Jain; Ser-Nam Lim; Rama Chellappa (CoRR, 2017)

Learning From Synthetic Data: Addressing Domain Shift for Semantic Segmentation. - Swami Sankaranarayanan; Yogesh Balaji; Arpit Jain; Ser Nam Lim; Rama Chellappa (CVPR, 2018)

Generate to Adapt: Aligning Domains Using Generative Adversarial Networks. - Swami Sankaranarayanan; Yogesh Balaji; Carlos Domingo Castillo; Rama Chellappa (CVPR, 2018)

MetaReg: Towards Domain Generalization using Meta-Regularization. - Yogesh Balaji; Swami Sankaranarayanan; Rama Chellappa (NeurIPS, 2018)

Normalized Wasserstein for Mixture Distributions With Applications in Adversarial Learning and Domain Adaptation. - Yogesh Balaji; Rama Chellappa; Soheil Feizi (ICCV, 2019)

Entropic GANs meet VAEs: A Statistical Approach to Compute Sample Likelihoods in GANs. - Yogesh Balaji; Hamed Hassani; Rama Chellappa; Soheil Feizi (ICML, 2019)

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

Normalized Wasserstein Distance for Mixture Distributions with Applications in Adversarial Learning and Domain Adaptation. - Yogesh Balaji; Rama Chellappa; Soheil Feizi (CoRR, 2019)

Instance adaptive adversarial training: Improved accuracy tradeoffs in neural nets. - Yogesh Balaji; Tom Goldstein; Judy Hoffman (CoRR, 2019)

Invert and Defend: Model-based Approximate Inversion of Generative Adversarial Networks for Secure Inference. - Wei-An Lin; Yogesh Balaji; Pouya Samangouei; Rama Chellappa (CoRR, 2019)

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

Learning to Balance Specificity and Invariance for In and Out of Domain Generalization. - Prithvijit Chattopadhyay; Yogesh Balaji; Judy Hoffman (ECCV (9), 2020)

Curriculum Manager for Source Selection in Multi-source Domain Adaptation. - Luyu Yang; Yogesh Balaji; Ser-Nam Lim; Abhinav Shrivastava (ECCV (14), 2020)

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

Mirrored Autoencoders with Simplex Interpolation for Unsupervised Anomaly Detection. - Yexin Wu; Yogesh Balaji; Bhanukiran Vinzamuri; Soheil Feizi (CoRR, 2020)

The Effectiveness of Memory Replay in Large Scale Continual Learning. - Yogesh Balaji; Mehrdad Farajtabar; Dong Yin; Alex Mott; Ang Li (CoRR, 2020)

Winning Lottery Tickets in Deep Generative Models. - Neha Mukund Kalibhat; Yogesh Balaji; Soheil Feizi (AAAI, 2021)

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

Unsupervised anomaly detection with adversarial mirrored autoencoders. - Gowthami Somepalli; Yexin Wu; Yogesh Balaji; Bhanukiran Vinzamuri; Soheil Feizi (UAI, 2021)

Understanding Overparameterization in Generative Adversarial Networks. - Yogesh Balaji; Mohammadmahdi Sajedi; Neha Mukund Kalibhat; Mucong Ding; Dominik Stöger; Mahdi Soltanolkotabi; Soheil Feizi (CoRR, 2021)

Robust Learning under Distributional Shifts. - Yogesh Balaji (2021)

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

eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers. - Yogesh Balaji; Seungjun Nah; Xun Huang; Arash Vahdat; Jiaming Song; Karsten Kreis; Miika Aittala; Timo Aila; Samuli Laine; Bryan Catanzaro; Tero Karras; Ming-Yu Liu 001 (CoRR, 2022)

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 001; Jia-Bin Huang 001; Ming-Yu Liu 001; Yogesh Balaji (ICCV, 2023)

JeDi: Joint-Image Diffusion Models for Finetuning-Free Personalized Text-to-Image Generation. - Yu Zeng 001; Vishal M. Patel; Haochen Wang; Xun Huang; Ting-Chun Wang; Ming-Yu Liu 001; Yogesh Balaji (CVPR, 2024)

One-Step Diffusion Policy: Fast Visuomotor Policies via Diffusion Distillation. - Zhendong Wang; Zhaoshuo Li; Ajay Mandlekar; Zhenjia Xu; Jiaojiao Fan; Yashraj S. Narang; Linxi Fan; Yuke Zhu; Yogesh Balaji; Mingyuan Zhou; Ming-Yu Liu 001; Yu Zeng 001 (CoRR, 2024)

Edify Image: High-Quality Image Generation with Pixel Space Laplacian Diffusion Models. - Yuval Atzmon; Maciej Bala; Yogesh Balaji; Tiffany Cai; Yin Cui; Jiaojiao Fan; Yunhao Ge; Siddharth Gururani; Jacob Samuel Huffman; Ronald Isaac; Pooya Jannaty; Tero Karras; et al. (CoRR, 2024)

A Comprehensive Study of Decoder-Only LLMs for Text-to-Image Generation. - Andrew Z. Wang; Songwei Ge; Tero Karras; Ming-Yu Liu 001; Yogesh Balaji (CVPR, 2025)

Cosmos World Foundation Model Platform for Physical AI. - Niket Agarwal; Arslan Ali; Maciej Bala; Yogesh Balaji; Erik Barker; Tiffany Cai; Prithvijit Chattopadhyay; Yongxin Chen; Yin Cui; Yifan Ding; Daniel Dworakowski; Jiaojiao Fan; et al. (CoRR, 2025)