Yogesh Balaji

According to our database, Yogesh Balaji authored at least 27 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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

CoRR, 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

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

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

CoRR, 2022

A Comprehensive Study of Image Classification Model Sensitivity to Foregrounds, Backgrounds, and Visual Attributes.

Mazda Moayeri, Phillip Pope, Yogesh Balaji, Soheil Feizi

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Robust Learning under Distributional Shifts.

Yogesh Balaji

PhD thesis, 2021

Understanding Overparameterization in Generative Adversarial Networks.

Yogesh Balaji, Mohammadmahdi Sajedi, Neha Mukund Kalibhat, Mucong Ding, Dominik Stöger, Mahdi Soltanolkotabi, Soheil Feizi

CoRR, 2021

Unsupervised anomaly detection with adversarial mirrored autoencoders.

Gowthami Somepalli, Yexin Wu, Yogesh Balaji, Bhanukiran Vinzamuri, Soheil Feizi

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Understanding Over-parameterization in Generative Adversarial Networks.

Yogesh Balaji, Mohammadmahdi Sajedi, Neha Mukund Kalibhat, Mucong Ding, Dominik Stöger, Mahdi Soltanolkotabi, Soheil Feizi

Proceedings of the 9th International Conference on Learning Representations, 2021

Winning Lottery Tickets in Deep Generative Models.

Neha Mukund Kalibhat, Yogesh Balaji, Soheil Feizi

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

The Effectiveness of Memory Replay in Large Scale Continual Learning.

Yogesh Balaji, Mehrdad Farajtabar, Dong Yin, Alex Mott, Ang Li

CoRR, 2020

Mirrored Autoencoders with Simplex Interpolation for Unsupervised Anomaly Detection.

Yexin Wu, Yogesh Balaji, Bhanukiran Vinzamuri, Soheil Feizi

CoRR, 2020

Robust Optimal Transport with Applications in Generative Modeling and Domain Adaptation.

Yogesh Balaji, Rama Chellappa, Soheil Feizi

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Curriculum Manager for Source Selection in Multi-source Domain Adaptation.

Luyu Yang, Yogesh Balaji, Ser-Nam Lim, Abhinav Shrivastava

Proceedings of the Computer Vision - ECCV 2020, 2020

Learning to Balance Specificity and Invariance for In and Out of Domain Generalization.

Prithvijit Chattopadhyay, Yogesh Balaji, Judy Hoffman

Proceedings of the Computer Vision - ECCV 2020, 2020

Adversarial Robustness of Flow-Based Generative Models.

Phillip Pope, Yogesh Balaji, Soheil Feizi

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

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

Instance adaptive adversarial training: Improved accuracy tradeoffs in neural nets.

Yogesh Balaji, Tom Goldstein, Judy Hoffman

CoRR, 2019

Normalized Wasserstein Distance for Mixture Distributions with Applications in Adversarial Learning and Domain Adaptation.

Yogesh Balaji, Rama Chellappa, Soheil Feizi

CoRR, 2019

Conditional GAN with Discriminative Filter Generation for Text-to-Video Synthesis.

Yogesh Balaji, Martin Renqiang Min, Bing Bai, Rama Chellappa, Hans Peter Graf

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Entropic GANs meet VAEs: A Statistical Approach to Compute Sample Likelihoods in GANs.

Yogesh Balaji, Hamed Hassani, Rama Chellappa, Soheil Feizi

Proceedings of the 36th International Conference on Machine Learning, 2019

Normalized Wasserstein for Mixture Distributions With Applications in Adversarial Learning and Domain Adaptation.

Yogesh Balaji, Rama Chellappa, Soheil Feizi

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

2018

MetaReg: Towards Domain Generalization using Meta-Regularization.

Yogesh Balaji, Swami Sankaranarayanan, Rama Chellappa

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Generate to Adapt: Aligning Domains Using Generative Adversarial Networks.

Swami Sankaranarayanan, Yogesh Balaji, Carlos Domingo Castillo, Rama Chellappa

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Learning From Synthetic Data: Addressing Domain Shift for Semantic Segmentation.

Swami Sankaranarayanan, Yogesh Balaji, Arpit Jain, Ser Nam Lim, Rama Chellappa

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

Unsupervised Domain Adaptation for Semantic Segmentation with GANs.

Swami Sankaranarayanan, Yogesh Balaji, Arpit Jain, Ser-Nam Lim, Rama Chellappa

CoRR, 2017

Unrolling the Shutter: CNN to Correct Motion Distortions.

Vijay Rengarajan, Yogesh Balaji, A. N. Rajagopalan

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

Deep Decoupling of Defocus and Motion Blur for Dynamic Segmentation.

Abhijith Punnappurath, Yogesh Balaji, Mahesh Mohan M. R., Ambasamudram Narayanan Rajagopalan

Proceedings of the Computer Vision - ECCV 2016, 2016