Bin Dai

According to our database, Bin Dai authored at least 12 papers between 2017 and 2024.

Collaborative distances:

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

2024

Disentangling Planning, Driving and Rendering for Photorealistic Avatar Agents.

Duomin Wang, Bin Dai, Yu Deng, Baoyuan Wang

Proceedings of the Computer Vision - ECCV 2024 Workshops, 2024

2021

On the Value of Infinite Gradients in Variational Autoencoder Models.

Bin Dai, Wenliang Li, David P. Wipf

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

2020

Further Analysis of Outlier Detection with Deep Generative Models.

Ziyu Wang, Bin Dai, David P. Wipf, Jun Zhu

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

The Usual Suspects? Reassessing Blame for VAE Posterior Collapse.

Bin Dai, Ziyu Wang, David P. Wipf

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

2019

Diagnosing and Enhancing VAE Models.

Bin Dai, David P. Wipf

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Recurrent Variational Autoencoders for Learning Nonlinear Generative Models in the Presence of Outliers.

Yu Wang, Bin Dai, Gang Hua, John A. D. Aston, David P. Wipf

IEEE J. Sel. Top. Signal Process., 2018

Connections with Robust PCA and the Role of Emergent Sparsity in Variational Autoencoder Models.

Bin Dai, Yu Wang, John A. D. Aston, Gang Hua, David P. Wipf

J. Mach. Learn. Res., 2018

Compressing Neural Networks using the Variational Information Bottleneck.

Bin Dai, Chen Zhu, David P. Wipf

CoRR, 2018

Compressing Neural Networks using the Variational Information Bottleneck.

Bin Dai, Chen Zhu, Baining Guo, David P. Wipf

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Understanding and Predicting The Attractiveness of Human Action Shot.

Bin Dai, Baoyuan Wang, Gang Hua

CoRR, 2017

Veiled Attributes of the Variational Autoencoder.

Bin Dai, Yu Wang, John A. D. Aston, Gang Hua, David P. Wipf

CoRR, 2017

Green Generative Modeling: Recycling Dirty Data using Recurrent Variational Autoencoders.

Yu Wang, Bin Dai, Gang Hua, John A. D. Aston, David P. Wipf

Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017