Jiahao Zhang

11 papers Journal 11

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Relaxed Vector Auxiliary Variable Algorithm for Unconstrained Optimization Problems. SIAM J. Sci. Comput. Shiheng Zhang, Jiahao Zhang, Jie Shen, Guang Lin
2025	J	`jnl`	A self-adaptive energy-based learning rate for stochastic gradient descent via Vector Auxiliary Variable method. Eng. Appl. Artif. Intell. Jiahao Zhang, Christian Moya, Guang Lin
2025	J	`jnl`	Energy-Dissipative Evolutionary Kolmogorov-Arnold Networks for Complex PDE Systems. CoRR Guang Lin, Changhong Mou, Jiahao Zhang
2025	J	`jnl`	Energy-dissipative evolutionary Kolmogorov-Arnold networks for complex PDE systems. J. Comput. Phys. Guang Lin, Changhong Mou, Jiahao Zhang
2024	J	`jnl`	An Energy-Based Self-Adaptive Learning Rate for Stochastic Gradient Descent: Enhancing Unconstrained Optimization with VAV method. CoRR Jiahao Zhang, Christian Moya, Guang Lin
2024	J	`jnl`	Energy-dissipative evolutionary deep operator neural networks. J. Comput. Phys. Jiahao Zhang, Shiheng Zhang, Jie Shen, Guang Lin
2023	J	`jnl`	An Element-wise RSAV Algorithm for Unconstrained Optimization Problems. CoRR Shiheng Zhang, Jiahao Zhang, Jie Shen, Guang Lin
2023	J	`jnl`	Energy-Dissipative Evolutionary Deep Operator Neural Networks. CoRR Jiahao Zhang, Shiheng Zhang, Jie Shen, Guang Lin
2022	J	`jnl`	MultiAuto-DeepONet: A Multi-resolution Autoencoder DeepONet for Nonlinear Dimension Reduction, Uncertainty Quantification and Operator Learning of Forward and Inverse Stochastic Problems. CoRR Jiahao Zhang, Shiqi Zhang, Guang Lin
2022	J	`jnl`	PAGP: A physics-assisted Gaussian process framework with active learning for forward and inverse problems of partial differential equations. CoRR Jiahao Zhang, Shiqi Zhang, Guang Lin
2022	J	`jnl`	RMFGP: Rotated Multi-fidelity Gaussian process with Dimension Reduction for High-dimensional Uncertainty Quantification. CoRR Jiahao Zhang, Shiqi Zhang, Guang Lin