Jonathan P. Williams

13 papers Journal 9Unranked 4
YearRankTypeTitle / Venue / Authors
2026 J jnl
Generalized fiducial inference on differentiable manifolds.
Int. J. Approx. Reason.
Alexander C. Murph, Jonathan P. Williams, Jan Hannig
2025 J jnl
Asymptotic efficiency of inferential models and a possibilistic Bernstein-von Mises theorem.
Int. J. Approx. Reason.
Ryan Martin, Jonathan P. Williams
2025 J jnl
Beyond Time-Homogeneity for Continuous-Time Multistate Markov Models.
J. Comput. Graph. Stat.
Emmett B. Kendall, Jonathan P. Williams, Gudmund Horn Hermansen, Frédéric Y. Bois, Vo Hong Thanh
2025 J jnl
Uncertainty quantification in automated valuation models with spatially weighted conformal prediction.
Int. J. Data Sci. Anal.
Anders Hjort, Gudmund Horn Hermansen, Johan Pensar, Jonathan P. Williams
2024 — conf
Clustered Conformal Prediction for the Housing Market.
COPA
Anders Hjort, Jonathan P. Williams, Johan Pensar
2024 — conf
Decision Theory via Model-Free Generalized Fiducial Inference.
BELIEF
Jonathan P. Williams, Yang Liu
2024 — conf
Large-Sample Theory for Inferential Models: A Possibilistic Bernstein-von Mises Theorem.
BELIEF
Ryan Martin, Jonathan P. Williams
2024 J jnl
Transfer Learning with Uncertainty Quantification: Random Effect Calibration of Source to Target (RECaST).
J. Mach. Learn. Res.
Jimmy Hickey, Jonathan P. Williams, Emily C. Hector
2023 J jnl
Model-free generalized fiducial inference.
CoRR
Jonathan P. Williams
2023 J jnl
Uncertainty quantification in automated valuation models with locally weighted conformal prediction.
CoRR
Anders Hjort, Gudmund Horn Hermansen, Johan Pensar, Jonathan P. Williams
2023 J jnl
Valid Inference for Machine Learning Model Parameters.
CoRR
Neil Dey, Jonathan P. Williams
2021 J jnl
Conformal prediction for text infilling and part-of-speech prediction.
CoRR
Neil Dey, Jing Ding, Jack Ferrell, Carolina Kapper, Maxwell Lovig, Emiliano Planchon, Jonathan P. Williams
2015 — conf
Covariance Selection in the Linear Mixed Effect Mode.
FE@NIPS
Jonathan P. Williams, Ying Lu