3 papers
cs.LG2025
Instance-Dependent Continuous-Time Reinforcement Learning via Maximum Likelihood Estimation
Runze Zhao, Yue Yu, Ruhan Wang +2
Continuous-time reinforcement learning (CTRL) provides a natural framework for sequential decision-making in dynamic environments where interactions evolve continuously over time.…
stat.ME2025
Intrinsic Random Functions and Parametric Covariance Models of Spatio-Temporal Random Processes on the Sphere
Jongwook Kim, Chunfeng Huang, Nicholas Bussberg
Identifying an appropriate covariance function is one of the primary interests in spatial and spatio-temporal statistics because it allows researchers to analyze the dependence str…
stat.ML2025
Issues with Neural Tangent Kernel Approach to Neural Networks
Haoran Liu, Anthony Tai, David J. Crandall +1
Neural tangent kernels (NTKs) have been proposed to study the behavior of trained neural networks from the perspective of Gaussian processes. An important result in this body of wo…