Search Results for author:
Found 8 papers, 3 papers with code
Using Sentence-Level LSTM Language Models for Script Inference
There is a small but growing body of research on statistical scripts, models of event sequences that allow probabilistic inference of implicit events from documents.
Better Conditional Density Estimation for Neural Networks
CDE Trend Filtering applies a k-th order graph trend filtering penalty to the unnormalized logits of a multinomial classifier network, with each edge in the graph corresponding to a neighboring point on a discretized version of the density.
Deep Nonparametric Estimation of Discrete Conditional Distributions via Smoothed Dyadic Partitioning
We present an approach to deep estimation of discrete conditional probability distributions.
Benchmarking Hierarchical Script Knowledge
Understanding procedural language requires reasoning about both hierarchical and temporal relations between events.
Does BERT Pretrained on Clinical Notes Reveal Sensitive Data?
The cost of training such models (and the necessity of data access to do so) coupled with their utility motivates parameter sharing, i. e., the release of pretrained models such as ClinicalBERT.
