3 papers
stat.ML2026
LLMs as Implicit Imputers: Uncertainty Should Scale with Missing Information
Stef van Buuren
Large language models (LLMs) are increasingly deployed in settings where the available context is incomplete or degraded. We argue that an LLM generating answers under incomplete c…
stat.ME2026
HIMCE: High-dimensional multiple imputation via covariance-mode updating for neuroimaging and spatiotemporal blocks
Hsin-Hsiung Huang, Stef van Buuren
High-dimensional neuroimaging and spatiotemporal blocks often contain structured missingness from acquisition artifacts, preprocessing failures, and sensor dropout. Multiple imputa…
stat.ME2024
Random Indicator Imputation for Missing Not At Random Data
Shahab Jolani, Stef van Buuren
Imputation methods for dealing with incomplete data typically assume that the missingness mechanism is at random (MAR). These methods can also be applied to missing not at random (…