DeepAI AI Chat
Log In Sign Up

Neural Conditional Event Time Models

by   Matthew Engelhard, et al.

Event time models predict occurrence times of an event of interest based on known features. Recent work has demonstrated that neural networks achieve state-of-the-art event time predictions in a variety of settings. However, standard event time models suppose that the event occurs, eventually, in all cases. Consequently, no distinction is made between a) the probability of event occurrence, and b) the predicted time of occurrence. This distinction is critical when predicting medical diagnoses, equipment defects, social media posts, and other events that or may not occur, and for which the features affecting a) may be different from those affecting b). In this work, we develop a conditional event time model that distinguishes between these components, implement it as a neural network with a binary stochastic layer representing finite event occurrence, and show how it may be learned from right-censored event times via maximum likelihood estimation. Results demonstrate superior event occurrence and event time predictions on synthetic data, medical events (MIMIC-III), and social media posts (Reddit), comprising 21 total prediction tasks.


page 1

page 2

page 3

page 4


Bayesian Neural Hawkes Process for Event Uncertainty Prediction

Many applications comprise of sequences of event data with the time of o...

Linking Sequences of Events with Sparse or No Common Occurrence across Data Sets

Data of practical interest - such as personal records, transaction logs,...

Predicting extreme events from data using deep machine learning: when and where

We develop a deep convolutional neural network (DCNN) based framework fo...

Predicting Times to Event Based on Vine Copula Models

In statistics, time-to-event analysis methods traditionally focus on the...

Temporal Reasoning with Probabilities

In this paper we explore representations of temporal knowledge based upo...

Sub-event detection from Twitter streams as a sequence labeling problem

This paper introduces improved methods for sub-event detection in social...

The statistical physics of discovering exogenous and endogenous factors in a chain of events

Event occurrence is not only subject to the environmental changes, but i...