Ching-Yao Chuang

According to our database, Ching-Yao Chuang authored at least 18 papers between 2017 and 2024.

Collaborative distances:

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

2024

Movie Gen: A Cast of Media Foundation Models.

Adam Polyak, Amit Zohar, Andrew Brown, Andros Tjandra, Animesh Sinha, Ann Lee, Apoorv Vyas, Bowen Shi, Chih-Yao Ma, Ching-Yao Chuang, David Yan, Dhruv Choudhary, Dingkang Wang, Geet Sethi, Guan Pang, Haoyu Ma, Ishan Misra, Ji Hou, Jialiang Wang, Kiran Jagadeesh, Kunpeng Li, Luxin Zhang, Mannat Singh, Mary Williamson, Matt Le, Matthew Yu, Mitesh Kumar Singh, Peizhao Zhang, Peter Vajda, Quentin Duval, Rohit Girdhar, Roshan Sumbaly, Sai Saketh Rambhatla, Sam S. Tsai, Samaneh Azadi, Samyak Datta, Sanyuan Chen, Sean Bell, Sharadh Ramaswamy, Shelly Sheynin, Siddharth Bhattacharya, Simran Motwani, Tao Xu, Tianhe Li, Tingbo Hou, Wei-Ning Hsu, Xi Yin, Xiaoliang Dai, Yaniv Taigman, Yaqiao Luo, Yen-Cheng Liu, Yi-Chiao Wu, Yue Zhao, Yuval Kirstain, Zecheng He, Zijian He, Albert Pumarola, Ali K. Thabet, Artsiom Sanakoyeu, Arun Mallya, Baishan Guo, Boris Araya, Breena Kerr, Carleigh Wood, Ce Liu, Cen Peng, Dmitry Vengertsev, Edgar Schönfeld, Elliot Blanchard, Felix Juefei-Xu, Fraylie Nord, Jeff Liang, John Hoffman, Jonas Kohler, Kaolin Fire, Karthik Sivakumar, Lawrence Chen, Licheng Yu, Luya Gao, Markos Georgopoulos, Rashel Moritz, Sara K. Sampson, Shikai Li, Simone Parmeggiani, Steve Fine, Tara Fowler, Vladan Petrovic, Yuming Du

CoRR, 2024

Fairy: Fast Parallelized Instruction-Guided Video-to-Video Synthesis.

Bichen Wu, Ching-Yao Chuang, Xiaoyan Wang, Yichen Jia, Kapil Krishnakumar, Tong Xiao, Feng Liang, Licheng Yu, Peter Vajda

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Robust Learning from Uncurated Data

Ching-Yao Chuang

PhD thesis, 2023

The Inductive Bias of Flatness Regularization for Deep Matrix Factorization.

Khashayar Gatmiry, Zhiyuan Li, Ching-Yao Chuang, Sashank J. Reddi, Tengyu Ma, Stefanie Jegelka

CoRR, 2023

Debiasing Vision-Language Models via Biased Prompts.

Ching-Yao Chuang, Varun Jampani, Yuanzhen Li, Antonio Torralba, Stefanie Jegelka

CoRR, 2023

What is the Inductive Bias of Flatness Regularization? A Study of Deep Matrix Factorization Models.

Khashayar Gatmiry, Zhiyuan Li, Tengyu Ma, Sashank J. Reddi, Stefanie Jegelka, Ching-Yao Chuang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

InfoOT: Information Maximizing Optimal Transport.

Ching-Yao Chuang, Stefanie Jegelka, David Alvarez-Melis

Proceedings of the International Conference on Machine Learning, 2023

2022

Tree Mover's Distance: Bridging Graph Metrics and Stability of Graph Neural Networks.

Ching-Yao Chuang, Stefanie Jegelka

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Robust Contrastive Learning against Noisy Views.

Ching-Yao Chuang, R. Devon Hjelm, Xin Wang, Vibhav Vineet, Neel Joshi, Antonio Torralba, Stefanie Jegelka, Yale Song

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

2021

Measuring Generalization with Optimal Transport.

Ching-Yao Chuang, Youssef Mroueh, Kristjan H. Greenewald, Antonio Torralba, Stefanie Jegelka

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Contrastive Learning with Hard Negative Samples.

Joshua David Robinson, Ching-Yao Chuang, Suvrit Sra, Stefanie Jegelka

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

Fair Mixup: Fairness via Interpolation.

Ching-Yao Chuang, Youssef Mroueh

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

2020

Debiased Contrastive Learning.

Ching-Yao Chuang, Joshua Robinson, Yen-Chen Lin, Antonio Torralba, Stefanie Jegelka

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

Estimating Generalization under Distribution Shifts via Domain-Invariant Representations.

Ching-Yao Chuang, Antonio Torralba, Stefanie Jegelka

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

The Role of Embedding Complexity in Domain-invariant Representations.

Ching-Yao Chuang, Antonio Torralba, Stefanie Jegelka

CoRR, 2019

2018

Learning to Act Properly: Predicting and Explaining Affordances From Images.

Ching-Yao Chuang, Jiaman Li, Antonio Torralba, Sanja Fidler

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

2017

Show, Adapt and Tell: Adversarial Training of Cross-Domain Image Captioner.

Tseng-Hung Chen, Yuan-Hong Liao, Ching-Yao Chuang, Wan Ting Hsu, Jianlong Fu, Min Sun

Proceedings of the IEEE International Conference on Computer Vision, 2017

Leveraging Video Descriptions to Learn Video Question Answering.

Kuo-Hao Zeng, Tseng-Hung Chen, Ching-Yao Chuang, Yuan-Hong Liao, Juan Carlos Niebles, Min Sun

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017