Zhi Chen

Orcid: 0000-0003-1993-5749

Affiliations:
  • Duke University, Durham, NC, USA
  • Nanjing University, Nanjing, Jiangsu, China (former)


According to our database1, Zhi Chen authored at least 15 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Phononic materials with effectively scale-separated hierarchical features using interpretable machine learning.
CoRR, 2024

Sparse and Faithful Explanations Without Sparse Models.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023
Human-in-the-loop Machine Learning System via Model Interpretability.
PhD thesis, 2023

Understanding and Exploring the Whole Set of Good Sparse Generalized Additive Models.
CoRR, 2023

Exploring and Interacting with the Set of Good Sparse Generalized Additive Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Missing Values and Imputation in Healthcare Data: Can Interpretable Machine Learning Help?
Proceedings of the Conference on Health, Inference, and Learning, 2023

2022
SegDiscover: Visual Concept Discovery via Unsupervised Semantic Segmentation.
CoRR, 2022

TimberTrek: Exploring and Curating Sparse Decision Trees with Interactive Visualization.
Proceedings of the 2022 IEEE Visualization and Visual Analytics (VIS), 2022

Exploring the Whole Rashomon Set of Sparse Decision Trees.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
2D elastodynamic metamaterials.
Dataset, November, 2021

How to See Hidden Patterns in Metamaterials with Interpretable Machine Learning.
CoRR, 2021

Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges.
CoRR, 2021

Using Explainable Boosting Machines (EBMs) to Detect Common Flaws in Data.
Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2021

2020
Concept whitening for interpretable image recognition.
Nat. Mach. Intell., 2020

2017
Adversarial Feature Matching for Text Generation.
Proceedings of the 34th International Conference on Machine Learning, 2017


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