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ORCIDYogesh Balaji
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2020 – today
- 2024
[c18]Yu Zeng, Vishal M. Patel, Haochen Wang, Xun Huang, Ting-Chun Wang, Ming-Yu Liu, Yogesh Balaji:
JeDi: Joint-Image Diffusion Models for Finetuning-Free Personalized Text-to-Image Generation. CVPR 2024: 6786-6795- [i20]Yu Zeng, Vishal M. Patel, Haochen Wang, Xun Huang, Ting-Chun Wang, Ming-Yu Liu, Yogesh Balaji:
JeDi: Joint-Image Diffusion Models for Finetuning-Free Personalized Text-to-Image Generation. CoRR abs/2407.06187 (2024) - [i19]Zhendong Wang, Zhaoshuo Li, Ajay Mandlekar, Zhenjia Xu, Jiaojiao Fan, Yashraj S. Narang, Linxi Fan, Yuke Zhu, Yogesh Balaji, Mingyuan Zhou, Ming-Yu Liu, Yu Zeng:
One-Step Diffusion Policy: Fast Visuomotor Policies via Diffusion Distillation. CoRR abs/2410.21257 (2024) - [i18]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, Grace Lam, J. P. Lewis, Aaron Licata, Yen-Chen Lin, Ming-Yu Liu, Qianli Ma, Arun Mallya, Ashlee Martino-Tarr, Doug Mendez, Seungjun Nah, Chris Pruett, Fitsum Reda, Jiaming Song, Ting-Chun Wang, Fangyin Wei, Xiaohui Zeng, Yu Zeng, Qinsheng Zhang:
Edify Image: High-Quality Image Generation with Pixel Space Laplacian Diffusion Models. CoRR abs/2411.07126 (2024) - 2023
- [c17]Songwei Ge, Seungjun Nah, Guilin Liu, Tyler Poon, Andrew Tao, Bryan Catanzaro, David Jacobs, Jia-Bin Huang, Ming-Yu Liu, Yogesh Balaji:
Preserve Your Own Correlation: A Noise Prior for Video Diffusion Models. ICCV 2023: 22873-22884 - [i17]Songwei Ge, Seungjun Nah, Guilin Liu, Tyler Poon, Andrew Tao, Bryan Catanzaro, David Jacobs, Jia-Bin Huang, Ming-Yu Liu, Yogesh Balaji:
Preserve Your Own Correlation: A Noise Prior for Video Diffusion Models. CoRR abs/2305.10474 (2023) - 2022
- [c16]Mazda Moayeri, Phillip Pope, Yogesh Balaji, Soheil Feizi:
A Comprehensive Study of Image Classification Model Sensitivity to Foregrounds, Backgrounds, and Visual Attributes. CVPR 2022: 19065-19075 - [i16]Mazda Moayeri, Phillip Pope, Yogesh Balaji, Soheil Feizi:
A Comprehensive Study of Image Classification Model Sensitivity to Foregrounds, Backgrounds, and Visual Attributes. CoRR abs/2201.10766 (2022) - [i15]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:
eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers. CoRR abs/2211.01324 (2022) - 2021
- [b1]Yogesh Balaji:
Robust Learning under Distributional Shifts. University of Maryland, College Park, MD, USA, 2021 - [c15]Neha Mukund Kalibhat, Yogesh Balaji, Soheil Feizi:
Winning Lottery Tickets in Deep Generative Models. AAAI 2021: 8038-8046 - [c14]Yogesh Balaji, Mohammadmahdi Sajedi, Neha Mukund Kalibhat, Mucong Ding, Dominik Stöger, Mahdi Soltanolkotabi
, Soheil Feizi:
Understanding Over-parameterization in Generative Adversarial Networks. ICLR 2021 - [c13]Gowthami Somepalli, Yexin Wu, Yogesh Balaji, Bhanukiran Vinzamuri, Soheil Feizi:
Unsupervised anomaly detection with adversarial mirrored autoencoders. UAI 2021: 365-375 - [i14]Yogesh Balaji, Mohammadmahdi Sajedi, Neha Mukund Kalibhat, Mucong Ding, Dominik Stöger, Mahdi Soltanolkotabi, Soheil Feizi:
Understanding Overparameterization in Generative Adversarial Networks. CoRR abs/2104.05605 (2021) - 2020
- [c12]Phillip Pope, Yogesh Balaji, Soheil Feizi:
Adversarial Robustness of Flow-Based Generative Models. AISTATS 2020: 3795-3805 - [c11]Prithvijit Chattopadhyay, Yogesh Balaji, Judy Hoffman:
Learning to Balance Specificity and Invariance for In and Out of Domain Generalization. ECCV (9) 2020: 301-318 - [c10]Luyu Yang, Yogesh Balaji, Ser-Nam Lim, Abhinav Shrivastava:
Curriculum Manager for Source Selection in Multi-source Domain Adaptation. ECCV (14) 2020: 608-624 - [c9]Yogesh Balaji, Rama Chellappa, Soheil Feizi:
Robust Optimal Transport with Applications in Generative Modeling and Domain Adaptation. NeurIPS 2020 - [i13]Yexin Wu, Yogesh Balaji, Bhanukiran Vinzamuri, Soheil Feizi:
Mirrored Autoencoders with Simplex Interpolation for Unsupervised Anomaly Detection. CoRR abs/2003.10713 (2020) - [i12]Luyu Yang, Yogesh Balaji, Ser-Nam Lim, Abhinav Shrivastava:
Curriculum Manager for Source Selection in Multi-Source Domain Adaptation. CoRR abs/2007.01261 (2020) - [i11]Prithvijit Chattopadhyay, Yogesh Balaji, Judy Hoffman:
Learning to Balance Specificity and Invariance for In and Out of Domain Generalization. CoRR abs/2008.12839 (2020) - [i10]Neha Mukund Kalibhat, Yogesh Balaji, Soheil Feizi:
Winning Lottery Tickets in Deep Generative Models. CoRR abs/2010.02350 (2020) - [i9]Yogesh Balaji, Mehrdad Farajtabar, Dong Yin, Alex Mott, Ang Li:
The Effectiveness of Memory Replay in Large Scale Continual Learning. CoRR abs/2010.02418 (2020) - [i8]Yogesh Balaji, Rama Chellappa, Soheil Feizi:
Robust Optimal Transport with Applications in Generative Modeling and Domain Adaptation. CoRR abs/2010.05862 (2020)
2010 – 2019
- 2019
- [c8]Yogesh Balaji, Rama Chellappa, Soheil Feizi:
Normalized Wasserstein for Mixture Distributions With Applications in Adversarial Learning and Domain Adaptation. ICCV 2019: 6499-6507 - [c7]Yogesh Balaji, Hamed Hassani, Rama Chellappa, Soheil Feizi:
Entropic GANs meet VAEs: A Statistical Approach to Compute Sample Likelihoods in GANs. ICML 2019: 414-423 - [c6]Yogesh Balaji, Martin Renqiang Min, Bing Bai, Rama Chellappa, Hans Peter Graf:
Conditional GAN with Discriminative Filter Generation for Text-to-Video Synthesis. IJCAI 2019: 1995-2001 - [i7]Yogesh Balaji, Rama Chellappa, Soheil Feizi:
Normalized Wasserstein Distance for Mixture Distributions with Applications in Adversarial Learning and Domain Adaptation. CoRR abs/1902.00415 (2019) - [i6]Yogesh Balaji, Tom Goldstein, Judy Hoffman:
Instance adaptive adversarial training: Improved accuracy tradeoffs in neural nets. CoRR abs/1910.08051 (2019) - [i5]Phillip Pope, Yogesh Balaji, Soheil Feizi:
Adversarial Robustness of Flow-Based Generative Models. CoRR abs/1911.08654 (2019) - [i4]Wei-An Lin, Yogesh Balaji, Pouya Samangouei, Rama Chellappa:
Invert and Defend: Model-based Approximate Inversion of Generative Adversarial Networks for Secure Inference. CoRR abs/1911.10291 (2019) - 2018
- [c5]Swami Sankaranarayanan, Yogesh Balaji, Arpit Jain, Ser Nam Lim, Rama Chellappa:
Learning From Synthetic Data: Addressing Domain Shift for Semantic Segmentation. CVPR 2018: 3752-3761 - [c4]Swami Sankaranarayanan, Yogesh Balaji, Carlos Domingo Castillo, Rama Chellappa:
Generate to Adapt: Aligning Domains Using Generative Adversarial Networks. CVPR 2018: 8503-8512 - [c3]Yogesh Balaji, Swami Sankaranarayanan, Rama Chellappa:
MetaReg: Towards Domain Generalization using Meta-Regularization. NeurIPS 2018: 1006-1016 - [i3]Yogesh Balaji, Hamed Hassani, Rama Chellappa, Soheil Feizi:
Entropic GANs meet VAEs: A Statistical Approach to Compute Sample Likelihoods in GANs. CoRR abs/1810.04147 (2018) - 2017
- [c2]Vijay Rengarajan, Yogesh Balaji, A. N. Rajagopalan:
Unrolling the Shutter: CNN to Correct Motion Distortions. CVPR 2017: 2345-2353 - [i2]Swami Sankaranarayanan, Yogesh Balaji, Carlos Domingo Castillo, Rama Chellappa:
Generate To Adapt: Aligning Domains using Generative Adversarial Networks. CoRR abs/1704.01705 (2017) - [i1]Swami Sankaranarayanan, Yogesh Balaji, Arpit Jain, Ser-Nam Lim, Rama Chellappa:
Unsupervised Domain Adaptation for Semantic Segmentation with GANs. CoRR abs/1711.06969 (2017) - 2016
- [c1]Abhijith Punnappurath, Yogesh Balaji, Mahesh Mohan M. R., Ambasamudram Narayanan Rajagopalan:
Deep Decoupling of Defocus and Motion Blur for Dynamic Segmentation. ECCV (7) 2016: 750-765
Coauthor Index
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