Zebin Yang

Wells Fargo (United States) — United States

Computer Science · Physical Sciences

10h-index657citations27works0.72yr avg
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Research Topics

Neural Networks and Applications(11), Machine Learning and ELM(8), Adversarial Robustness in Machine Learning(5), Explainable Artificial Intelligence (XAI)(5), Energy Load and Power Forecasting(4)

Publications27 total

Stable Subsampling under Model Misspecification and Covariate Shift
ACM Transactions on Knowledge Discovery from Data·2025
Interpretable Machine Learning Based on Functional ANOVA Framework: Algorithms and Comparisons
Applied Stochastic Models in Business and Industry·2025· 2 cited
Inherently Interpretable Tree Ensemble Learning
arXiv (Cornell University)·2024Open Access
The Anatomy of Mortgage Default Using Shape-Constrained Explainable Machine Learning Model
The Journal of Financial Data Science·2023· 2 cited
A Sequential Stein’s Method for Faster Training of Additive Index Models
IEEE Transactions on Neural Networks and Learning Systems·2023
PiML Toolbox for Interpretable Machine Learning Model Development and Diagnostics
arXiv (Cornell University)·2023· 6 citedOpen Access
Efficient Model-Free Subsampling Method for Massive Data
Figshare·2023Open Access
Efficient Model-free Subsampling Method for Massive Data
Figshare·2023Open Access
GAMI-Net: An explainable neural network based on generalized additive models with structured interactions
Pattern Recognition·2021· 111 cited
An effective SteinGLM initialization scheme for training multi-layer feedforward sigmoidal neural networks
Neural Networks·2021· 4 cited
Single-Index Model Tree
IEEE Transactions on Knowledge and Data Engineering·2021· 2 cited
Explainable Recommendation Systems by Generalized Additive Models with Manifest and Latent Interactions
arXiv (Cornell University)·2020· 2 citedOpen Access
Unwrapping The Black Box of Deep ReLU Networks: Interpretability, Diagnostics, and Simplification
arXiv (Cornell University)·2020· 20 citedOpen Access
Enhancing Explainability of Neural Networks Through Architecture Constraints
IEEE Transactions on Neural Networks and Learning Systems·2020· 98 cited
An Effective and Efficient Initialization Scheme for Training Multi-layer Feedforward Neural Networks
arXiv (Cornell University)·2020Open Access
An Effective and Efficient Initialization Scheme for Multi-layer Feedforward Neural Networks.
arXiv (Cornell University)·2020Open Access
An Effective and Efficient Training Algorithm for Multi-layer Feedforward Neural Networks
arXiv (Cornell University)·2020Open Access
GAMI-Net: An Explainable Neural Network based on Generalized Additive Models with Structured Interactions
arXiv (Cornell University)·2020· 16 citedOpen Access
Enhancing Explainability of Neural Networks through Architecture Constraints
arXiv (Cornell University)·2019· 8 citedOpen Access
User Mining Algorithm Based On PageRank Modeling Improvement and Comprehensive Influence Evaluation
2018 IEEE 4th Information Technology and Mechatronics Engineering Conference (ITOEC)·2018· 1 cited
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Frequent Co-authors

Aijun Zhang(19), Agus Sudjianto(15), Hengtao Zhang(5), Lean Yu(4), Ling Tang(4), Yongdao Zhou(3), Dennis K. J. Lin(2), Yu Su(2), Zheng Zhou(2), Aijun Zhang(2), Yaqing Zhao(1), Rongxi Zhou(1), Mei Yu(1), Dan A. Ralescu(1), William Knauth(1), Rahul Singh(1), Ningzhou Zeng(1), Yifeng Guo(1), Lingling Hu(1), Vijayan N. Nair(1)