Yeonjong Shin

ON THE TRAINING AND GENERALIZATION OF DEEP OPERATOR NETWORKS

SIAM JOURNAL ON SCIENTIFIC COMPUTING, 46(4), C273–C296.

S-OPT: A POINTS SELECTION ALGORITHM FOR HYPER-REDUCTION IN REDUCED ORDER MODELS

SIAM JOURNAL ON SCIENTIFIC COMPUTING, 46(4), B474–B501.

tLaSDI: Thermodynamics-informed latent space dynamics identification

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 429.

Accelerating gradient descent and Adam via fractional gradients

Neural Networks, 161, 185–201.

ERROR ESTIMATES OF RESIDUAL MINIMIZATION USING NEURAL NETWORKS FOR LINEAR PDES

Journal of Machine Learning for Modeling and Computing, 4(4), 73–101.

Active Neuron Least Squares: A training method for multivariate rectified neural networks

SIAM Journal on Scientific Computing, 44(4), A2253–A2275.

Approximation rates of DeepONets for learning operators arising from advection–diffusion equations

Neural Networks, 153, 411–426.

Deep Kronecker neural networks: A general framework for neural networks with adaptive activation functions

Neurocomputing, 468, 165–180.

Effects of depth, width, and initialization: A convergence analysis of layer-wise training for deep linear neural networks

Analysis and Applications, 20(01), 73–119.

GFINNs: GENERIC formalism informed neural networks for deterministic and stochastic dynamical systems

Identification of Corrupted Data via $k$-Means Clustering for Function Approximation

CSIAM Transactions on Applied Mathematics, 2(1), 81–107.

Plateau Phenomenon in Gradient Descent Training of RELU Networks: Explanation, Quantification, and Avoidance

SIAM Journal on Scientific Computing, 43(5), A3438–A3468.

Dying ReLU and Initialization: Theory and Numerical Examples

Communications in Computational Physics, 28(5), 1671–1706.

On the Convergence of Physics Informed Neural Networks for Linear Second-Order Elliptic and Parabolic Type PDEs

Communications in Computational Physics, 28(5), 2042–2074.

TRAINABILITY OF ReLU NETWORKS AND DATA-DEPENDENT INITIALIZATION

Journal of Machine Learning for Modeling and Computing, 1(1), 39–74.

Sequential function approximation with noisy data

Journal of Computational Physics, 371, 363–381.

A Randomized Algorithm for Multivariate Function Approximation

SIAM Journal on Scientific Computing, 39(3), A983–A1002.

A Randomized Tensor Quadrature Method for High Dimensional Polynomial Approximation

SIAM Journal on Scientific Computing, 39(5), A1811–A1833.

Sparse Approximation using $\ell_1-\ell_2$ Minimization and Its Application to Stochastic Collocation

SIAM Journal on Scientific Computing, 39(1), A229–A254.

Correcting Data Corruption Errors for Multivariate Function Approximation

SIAM Journal on Scientific Computing, 38(4), A2492–A2511.

Nonadaptive Quasi-Optimal Points Selection for Least Squares Linear Regression

SIAM Journal on Scientific Computing, 38(1), A385–A411.

On a near optimal sampling strategy for least squares polynomial regression

Journal of Computational Physics, 326, 931–946.