Covariance Selection in the Linear Mixed Effect Mode. - Jonathan P. Williams; Ying Lu (FE@NIPS, 2015)

Conformal prediction for text infilling and part-of-speech prediction. - Neil Dey; Jing Ding; Jack Ferrell; Carolina Kapper; Maxwell Lovig; Emiliano Planchon; Jonathan P. Williams (CoRR, 2021)

Valid Inference for Machine Learning Model Parameters. - Neil Dey; Jonathan P. Williams (CoRR, 2023)

Model-free generalized fiducial inference. - Jonathan P. Williams (CoRR, 2023)

Uncertainty quantification in automated valuation models with locally weighted conformal prediction. - Anders Hjort; Gudmund Horn Hermansen; Johan Pensar; Jonathan P. Williams (CoRR, 2023)

Large-Sample Theory for Inferential Models: A Possibilistic Bernstein-von Mises Theorem. - Ryan Martin; Jonathan P. Williams (BELIEF, 2024)

Decision Theory via Model-Free Generalized Fiducial Inference. - Jonathan P. Williams; Yang Liu (BELIEF, 2024)

Clustered Conformal Prediction for the Housing Market. - Anders Hjort; Jonathan P. Williams; Johan Pensar (COPA, 2024)

Asymptotic efficiency of inferential models and a possibilistic Bernstein-von Mises theorem. - Ryan Martin; Jonathan P. Williams (Int. J. Approx. Reason., 2025)

Beyond Time-Homogeneity for Continuous-Time Multistate Markov Models. - Emmett B. Kendall; Jonathan P. Williams; Gudmund Horn Hermansen; Frédéric Y. Bois; Vo Hong Thanh (J. Comput. Graph. Stat., 2025)