Matthew P. Repasky

most citedNeural Stein critics with staged

L^{2}

-regularization

1 citations · 1 across the 2 of their papers we have counts for

collaborators

2 papers

stat.ML2023

Deep graph kernel point processes over networks

Zheng Dong, Matthew Repasky, Xiuyuan Cheng +1

Point process models are widely used for continuous-time discrete-event data, where each data point includes time and additional information called "marks," such as locations, node…

stat.ML2022★ 1 cited

Neural Stein critics with staged $L^{2}$ -regularization

Matthew Repasky, Xiuyuan Cheng, Yao Xie

Learning to differentiate model distributions from observed data is a fundamental problem in statistics and machine learning, and high-dimensional data remains a challenging settin…

Deep graph kernel point processes over networks

Neural Stein critics with staged L2-regularization

Neural Stein critics with staged $L^{2}$ -regularization