Kuo Gai

11 papers Journal 11

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Progressive Feedforward Collapse of ResNet Training. IEEE Trans. Neural Networks Learn. Syst. Sicong Wang, Kuo Gai, Shihua Zhang
2025	J	`jnl`	Feature Dynamics as Implicit Data Augmentation: A Depth-Decomposed View on Deep Neural Network Generalization. CoRR Tianyu Ruan, Kuo Gai, Shihua Zhang
2025	J	`jnl`	On Pseudospectral Concentration for Rank-1 Sampling. CoRR Kuo Gai, Bin Shi
2024	J	`jnl`	Analytical Solution of a Three-layer Network with a Matrix Exponential Activation Function. CoRR Kuo Gai, Shihua Zhang
2024	J	`jnl`	Matrix normal PCA for interpretable dimension reduction and graphical noise modeling. Pattern Recognit. Chihao Zhang, Kuo Gai, Shihua Zhang
2024	J	`jnl`	OTAD: An Optimal Transport-Induced Robust Model for Agnostic Adversarial Attack. CoRR Kuo Gai, Sicong Wang, Shihua Zhang
2024	J	`jnl`	Progressive Feedforward Collapse of ResNet Training. CoRR Sicong Wang, Kuo Gai, Shihua Zhang
2024	J	`jnl`	Tessellating the Latent Space for Non-Adversarial Generative Auto-Encoders. IEEE Trans. Pattern Anal. Mach. Intell. Kuo Gai, Shihua Zhang
2021	J	`jnl`	A Mathematical Principle of Deep Learning: Learn the Geodesic Curve in the Wasserstein Space. CoRR Kuo Gai, Shihua Zhang
2020	J	`jnl`	Tessellated Wasserstein Auto-Encoders. CoRR Kuo Gai, Shihua Zhang
2019	J	`jnl`	Matrix Normal PCA for Interpretable Dimension Reduction and Graphical Noise Modeling. CoRR Chihao Zhang, Kuo Gai, Shihua Zhang