Get our free extension to see links to code for papers anywhere online!

Chrome logo  Add to Chrome

Firefox logo Add to Firefox
Picture for Kun Zhang

Kun Zhang
Alert button

On the Opportunity of Causal Deep Generative Models: A Survey and Future Directions


Feb 03, 2023
Guanglin Zhou, Lina Yao, Xiwei Xu, Chen Wang, Liming Zhu, Kun Zhang

Add code
Alert button

Figure 1 for On the Opportunity of Causal Deep Generative Models: A Survey and Future Directions
Figure 2 for On the Opportunity of Causal Deep Generative Models: A Survey and Future Directions
Figure 3 for On the Opportunity of Causal Deep Generative Models: A Survey and Future Directions
Figure 4 for On the Opportunity of Causal Deep Generative Models: A Survey and Future Directions

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Salesforce CausalAI Library: A Fast and Scalable Framework for Causal Analysis of Time Series and Tabular Data


Jan 25, 2023
Devansh Arpit, Matthew Fernandez, Chenghao Liu, Weiran Yao, Wenzhuo Yang, Paul Josel, Shelby Heinecke, Eric Hu, Huan Wang, Stephen Hoi, Caiming Xiong, Kun Zhang, Juan Carlos Niebles

Add code
Alert button

Figure 1 for Salesforce CausalAI Library: A Fast and Scalable Framework for Causal Analysis of Time Series and Tabular Data
Figure 2 for Salesforce CausalAI Library: A Fast and Scalable Framework for Causal Analysis of Time Series and Tabular Data
Figure 3 for Salesforce CausalAI Library: A Fast and Scalable Framework for Causal Analysis of Time Series and Tabular Data
Figure 4 for Salesforce CausalAI Library: A Fast and Scalable Framework for Causal Analysis of Time Series and Tabular Data

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Increasing Fairness in Compromise on Accuracy via Weighted Vote with Learning Guarantees


Jan 25, 2023
Yijun Bian, Kun Zhang

Add code
Alert button

Figure 1 for Increasing Fairness in Compromise on Accuracy via Weighted Vote with Learning Guarantees
Figure 2 for Increasing Fairness in Compromise on Accuracy via Weighted Vote with Learning Guarantees
Figure 3 for Increasing Fairness in Compromise on Accuracy via Weighted Vote with Learning Guarantees
Figure 4 for Increasing Fairness in Compromise on Accuracy via Weighted Vote with Learning Guarantees
* 18 pages, 15 figures, and 6 tables 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Tier Balancing: Towards Dynamic Fairness over Underlying Causal Factors


Jan 21, 2023
Zeyu Tang, Yatong Chen, Yang Liu, Kun Zhang

Add code
Alert button

Figure 1 for Tier Balancing: Towards Dynamic Fairness over Underlying Causal Factors
Figure 2 for Tier Balancing: Towards Dynamic Fairness over Underlying Causal Factors
Figure 3 for Tier Balancing: Towards Dynamic Fairness over Underlying Causal Factors
Figure 4 for Tier Balancing: Towards Dynamic Fairness over Underlying Causal Factors
* The 11th International Conference on Learning Representations (ICLR 2023) 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

SmartBrush: Text and Shape Guided Object Inpainting with Diffusion Model


Dec 09, 2022
Shaoan Xie, Zhifei Zhang, Zhe Lin, Tobias Hinz, Kun Zhang

Add code
Alert button

Figure 1 for SmartBrush: Text and Shape Guided Object Inpainting with Diffusion Model
Figure 2 for SmartBrush: Text and Shape Guided Object Inpainting with Diffusion Model
Figure 3 for SmartBrush: Text and Shape Guided Object Inpainting with Diffusion Model
Figure 4 for SmartBrush: Text and Shape Guided Object Inpainting with Diffusion Model

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Causal Discovery in Linear Latent Variable Models Subject to Measurement Error


Nov 08, 2022
Yuqin Yang, AmirEmad Ghassami, Mohamed Nafea, Negar Kiyavash, Kun Zhang, Ilya Shpitser

Add code
Alert button

Figure 1 for Causal Discovery in Linear Latent Variable Models Subject to Measurement Error
Figure 2 for Causal Discovery in Linear Latent Variable Models Subject to Measurement Error
Figure 3 for Causal Discovery in Linear Latent Variable Models Subject to Measurement Error
Figure 4 for Causal Discovery in Linear Latent Variable Models Subject to Measurement Error
* Accepted at 36th Conference on Neural Information Processing Systems (NeurIPS 2022) 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural Networks


Nov 01, 2022
Yue Yu, Xuan Kan, Hejie Cui, Ran Xu, Yujia Zheng, Xiangchen Song, Yanqiao Zhu, Kun Zhang, Razieh Nabi, Ying Guo, Chao Zhang, Carl Yang

Add code
Alert button

Figure 1 for Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural Networks
Figure 2 for Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural Networks
Figure 3 for Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural Networks
Figure 4 for Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural Networks
* Work in progress 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Temporally Disentangled Representation Learning


Oct 24, 2022
Weiran Yao, Guangyi Chen, Kun Zhang

Add code
Alert button

Figure 1 for Temporally Disentangled Representation Learning
Figure 2 for Temporally Disentangled Representation Learning
Figure 3 for Temporally Disentangled Representation Learning
Figure 4 for Temporally Disentangled Representation Learning
* NeurIPS 2022. arXiv admin note: text overlap with arXiv:2202.04828 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Identifiability and Asymptotics in Learning Homogeneous Linear ODE Systems from Discrete Observations


Oct 12, 2022
Yuanyuan Wang, Wei Huang, Mingming Gong, Xi Geng, Tongliang Liu, Kun Zhang, Dacheng Tao

Add code
Alert button

Figure 1 for Identifiability and Asymptotics in Learning Homogeneous Linear ODE Systems from Discrete Observations
Figure 2 for Identifiability and Asymptotics in Learning Homogeneous Linear ODE Systems from Discrete Observations
Figure 3 for Identifiability and Asymptotics in Learning Homogeneous Linear ODE Systems from Discrete Observations
Figure 4 for Identifiability and Asymptotics in Learning Homogeneous Linear ODE Systems from Discrete Observations

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email
1
2
3
4
5
6
7
>>