3 papers
stat.ML2017
Deep Nonparametric Estimation of Discrete Conditional Distributions via Smoothed Dyadic Partitioning
Wesley Tansey, Karl Pichotta, James G. Scott
We present an approach to deep estimation of discrete conditional probability distributions. Such models have several applications, including generative modeling of audio, image, a…
stat.ML2016
Better Conditional Density Estimation for Neural Networks
Wesley Tansey, Karl Pichotta, James G. Scott
The vast majority of the neural network literature focuses on predicting point values for a given set of response variables, conditioned on a feature vector. In many cases we need…
cs.CL2016
Using Sentence-Level LSTM Language Models for Script Inference
Karl Pichotta, Raymond J. Mooney
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. These systems…