Wei Wayne Chen

Orcid: 0000-0002-3807-1862

Affiliations:
  • Northwestern University, Department of Mechanical Engineering, Evanston, IL, USA
  • Siemens Technology, Princeton, NJ, USA (2019 - 2021)
  • University of Maryland, Department of Mechanical Engineering, College Park, MD, USA (PhD 2019)


According to our database1, Wei Wayne Chen authored at least 14 papers between 2017 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

Online presence:

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Bibliography

2024
Generative Inverse Design of Metamaterials with Functional Responses by Interpretable Learning.
CoRR, 2024

2023
Data-Driven Design for Metamaterials and Multiscale Systems: A Review.
CoRR, 2023

2022
ET-AL: Entropy-Targeted Active Learning for Bias Mitigation in Materials Data.
CoRR, 2022

Uncertainty-aware Mixed-variable Machine Learning for Materials Design.
CoRR, 2022

T-METASET: Task-Aware Generation of Metamaterial Datasets by Diversity-Based Active Learning.
CoRR, 2022

Hierarchical Deep Generative Models for Design Under Free-Form Geometric Uncertainty.
CoRR, 2022

2021
Deep Generative Models for Geometric Design Under Uncertainty.
CoRR, 2021

IH-GAN: A Conditional Generative Model for Implicit Surface-Based Inverse Design of Cellular Structures.
CoRR, 2021

MO-PaDGAN: Reparameterizing Engineering Designs for augmented multi-objective optimization.
Appl. Soft Comput., 2021

PcDGAN: A Continuous Conditional Diverse Generative Adversarial Network For Inverse Design.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

2020
Airfoil Design Parameterization and Optimization using Bézier Generative Adversarial Networks.
CoRR, 2020

Adaptive Expansion Bayesian Optimization for Unbounded Global Optimization.
CoRR, 2020

2018
BézierGAN: Automatic Generation of Smooth Curves from Interpretable Low-Dimensional Parameters.
CoRR, 2018

2017
Active Expansion Sampling for Learning Feasible Domains in an Unbounded Input Space.
CoRR, 2017


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