Yeonjong Shin

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 29

Top Topics

Function Approximation

Numerical Examples

Top Venues

SIAM J. Sci. Comput.

J. Comput. Phys.

Neural Networks

Publications

Sanghyun Lee, Yeonjong Shin
On the Training and Generalization of Deep Operator Networks. SIAM J. Sci. Comput. 46 (4) (2024)
Christophe Bonneville, Xiaolong He, April Tran, Jun Sur Richard Park, William Fries, Daniel A. Messenger, Siu Wun Cheung, Yeonjong Shin, David M. Bortz, Debojyoti Ghosh, Jiun-Shyan Chen, Jonathan L. Belof, Youngsoo Choi
A Comprehensive Review of Latent Space Dynamics Identification Algorithms for Intrusive and Non-Intrusive Reduced-Order-Modeling. CoRR (2024)
Jessica T. Lauzon, Siu Wun Cheung, Yeonjong Shin, Youngsoo Choi, Dylan Matthew Copeland, Kevin Huynh
S-OPT: A Points Selection Algorithm for Hyper-Reduction in Reduced Order Models. SIAM J. Sci. Comput. 46 (4) (2024)
Jun Sur Richard Park, Siu Wun Cheung, Youngsoo Choi, Yeonjong Shin
tLaSDI: Thermodynamics-informed latent space dynamics identification. CoRR (2024)
Sanghyun Lee, Yeonjong Shin
On the training and generalization of deep operator networks. CoRR (2023)
Yeonjong Shin, Jérôme Darbon, George Em Karniadakis
Accelerating gradient descent and Adam via fractional gradients. Neural Networks 161 (2023)
Khemraj Shukla, Yeonjong Shin
Randomized Forward Mode of Automatic Differentiation for Optimization Algorithms. CoRR (2023)
Beichuan Deng, Yeonjong Shin, Lu Lu, Zhongqiang Zhang, George Em Karniadakis
Approximation rates of DeepONets for learning operators arising from advection-diffusion equations. Neural Networks 153 (2022)
Jessica T. Lauzon, Siu Wun Cheung, Yeonjong Shin, Youngsoo Choi, Dylan Matthew Copeland, Kevin Huynh
S-OPT: A Points Selection Algorithm for Hyper-Reduction in Reduced Order Models. CoRR (2022)
Mark Ainsworth, Yeonjong Shin
Active Neuron Least Squares: A Training Method for Multivariate Rectified Neural Networks. SIAM J. Sci. Comput. 44 (4) (2022)
Ameya D. Jagtap, Yeonjong Shin, Kenji Kawaguchi, George Em Karniadakis
Deep Kronecker neural networks: A general framework for neural networks with adaptive activation functions. Neurocomputing 468 (2022)
Zhen Zhang, Yeonjong Shin, George Em Karniadakis
GFINNs: GENERIC Formalism Informed Neural Networks for Deterministic and Stochastic Dynamical Systems. CoRR (2021)
Beichuan Deng, Yeonjong Shin, Lu Lu, Zhongqiang Zhang, George Em Karniadakis
Convergence rate of DeepONets for learning operators arising from advection-diffusion equations. CoRR (2021)
Yeonjong Shin, Jérôme Darbon, George Em Karniadakis
A Caputo fractional derivative-based algorithm for optimization. CoRR (2021)
Ameya D. Jagtap, Yeonjong Shin, Kenji Kawaguchi, George Em Karniadakis
Deep Kronecker neural networks: A general framework for neural networks with adaptive activation functions. CoRR (2021)
Mark Ainsworth, Yeonjong Shin
Plateau Phenomenon in Gradient Descent Training of RELU Networks: Explanation, Quantification, and Avoidance. SIAM J. Sci. Comput. 43 (5) (2021)
Yeonjong Shin, Zhongqiang Zhang, George Em Karniadakis
Error estimates of residual minimization using neural networks for linear PDEs. CoRR (2020)
Mark Ainsworth, Yeonjong Shin
Plateau Phenomenon in Gradient Descent Training of ReLU networks: Explanation, Quantification and Avoidance. CoRR (2020)
Yeonjong Shin, Jérôme Darbon, George Em Karniadakis
On the Convergence and generalization of Physics Informed Neural Networks. CoRR (2020)
Yeonjong Shin, George E. Karniadakis
Trainability and Data-dependent Initialization of Over-parameterized ReLU Neural Networks. CoRR (2019)
Lu Lu, Yeonjong Shin, Yanhui Su, George E. Karniadakis
Dying ReLU and Initialization: Theory and Numerical Examples. CoRR (2019)
Yeonjong Shin
Effects of Depth, Width, and Initialization: A Convergence Analysis of Layer-wise Training for Deep Linear Neural Networks. CoRR (2019)
Yeonjong Shin, Kailiang Wu, Dongbin Xiu
Sequential function approximation with noisy data. J. Comput. Phys. 371 (2018)
Kailiang Wu, Yeonjong Shin, Dongbin Xiu
A Randomized Tensor Quadrature Method for High Dimensional Polynomial Approximation. SIAM J. Sci. Comput. 39 (5) (2017)
Yeonjong Shin, Dongbin Xiu
A Randomized Algorithm for Multivariate Function Approximation. SIAM J. Sci. Comput. 39 (3) (2017)
Liang Yan, Yeonjong Shin, Dongbin Xiu
Minimization and Its Application to Stochastic Collocation. SIAM J. Sci. Comput. 39 (1) (2017)
Yeonjong Shin, Dongbin Xiu
Nonadaptive Quasi-Optimal Points Selection for Least Squares Linear Regression. SIAM J. Sci. Comput. 38 (1) (2016)
Yeonjong Shin, Dongbin Xiu
Correcting Data Corruption Errors for Multivariate Function Approximation. SIAM J. Sci. Comput. 38 (4) (2016)
Yeonjong Shin, Dongbin Xiu
On a near optimal sampling strategy for least squares polynomial regression. J. Comput. Phys. 326 (2016)