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ORCIDBin Dai 0008
Person information
- affiliation: Xiaobing.AI, Boston, USA
Other persons with the same name
- Bin Dai — disambiguation page
- Bin Dai 0001
![[0000-0001-9405-2626]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0001-9405-2626")
— National University of Defense Technology, Unmanned System Institute, Changsha, China - Bin Dai 0002 — Huazhong University of Science and Technology, School of Electronic Information and Communications, Wuhan, China (and 2 more)
- Bin Dai 0003 — Southwest Jiaotong University, School of Information Science and Technology, Chengdu, China (and 3 more)
- Bin Dai 0004 — Beihang University, School of Electronic and Information Engineering, Beijing, China
- Bin Dai 0005 — Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, China
- Bin Dai 0006 — Economics and Management School, Wuhan University, Wuhan, China
- Bin Dai 0007 — Xiamen University of Technology, China, China
- Bin Dai 0009 — Hangzhou Innovation Institute, Beihang University, Hangzhou, China
- Bin Dai 0010 — National University of Defense Technology, Changsha, China
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2020 – today
- 2024
[c8]Duomin Wang, Bin Dai, Yu Deng, Baoyuan Wang:
Disentangling Planning, Driving and Rendering for Photorealistic Avatar Agents. ECCV Workshops (14) 2024: 137-147- 2021
- [c7]Bin Dai, Wenliang Li, David P. Wipf:
On the Value of Infinite Gradients in Variational Autoencoder Models. NeurIPS 2021: 7180-7192 - 2020
- [c6]Ziyu Wang, Bin Dai, David Wipf, Jun Zhu:
Further Analysis of Outlier Detection with Deep Generative Models. ICBINB@NeurIPS 2020: 11-20 - [c5]Bin Dai, Ziyu Wang, David P. Wipf:
The Usual Suspects? Reassessing Blame for VAE Posterior Collapse. ICML 2020: 2313-2322 - [c4]Ziyu Wang, Bin Dai, David P. Wipf, Jun Zhu:
Further Analysis of Outlier Detection with Deep Generative Models. NeurIPS 2020 - [i6]Ziyu Wang, Bin Dai, David P. Wipf, Jun Zhu:
Further Analysis of Outlier Detection with Deep Generative Models. CoRR abs/2010.13064 (2020)
2010 – 2019
- 2019
- [c3]Bin Dai, David P. Wipf:
Diagnosing and Enhancing VAE Models. ICLR (Poster) 2019 - [i5]Bin Dai, David P. Wipf:
Diagnosing and Enhancing VAE Models. CoRR abs/1903.05789 (2019) - [i4]Bin Dai, Ziyu Wang, David P. Wipf:
The Usual Suspects? Reassessing Blame for VAE Posterior Collapse. CoRR abs/1912.10702 (2019) - 2018
- [j2]Bin Dai, Yu Wang, John A. D. Aston, Gang Hua, David P. Wipf:
Connections with Robust PCA and the Role of Emergent Sparsity in Variational Autoencoder Models. J. Mach. Learn. Res. 19: 41:1-41:42 (2018) - [j1]Yu Wang, Bin Dai, Gang Hua, John A. D. Aston, David P. Wipf:
Recurrent Variational Autoencoders for Learning Nonlinear Generative Models in the Presence of Outliers. IEEE J. Sel. Top. Signal Process. 12(6): 1615-1627 (2018) - [c2]Bin Dai, Chen Zhu, Baining Guo, David P. Wipf:
Compressing Neural Networks using the Variational Information Bottleneck. ICML 2018: 1143-1152 - [i3]Bin Dai, Chen Zhu, David P. Wipf:
Compressing Neural Networks using the Variational Information Bottleneck. CoRR abs/1802.10399 (2018) - 2017
- [c1]Yu Wang, Bin Dai, Gang Hua, John A. D. Aston, David P. Wipf:
Green Generative Modeling: Recycling Dirty Data using Recurrent Variational Autoencoders. UAI 2017 - [i2]Bin Dai, Yu Wang, John A. D. Aston, Gang Hua, David P. Wipf:
Veiled Attributes of the Variational Autoencoder. CoRR abs/1706.05148 (2017) - [i1]Bin Dai, Baoyuan Wang, Gang Hua:
Understanding and Predicting The Attractiveness of Human Action Shot. CoRR abs/1711.00677 (2017)
Coauthor Index
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