77 citations · 118 across the 6 of their papers we have counts for
3 papers · 1 filter
Intermittent Demand Forecasting with Deep Renewal Processes
Ali Caner Turkmen, Yuyang Wang, Tim Januschowski
Intermittent demand, where demand occurrences appear sporadically in time, is a common and challenging problem in forecasting. In this paper, we first make the connections between…
A Bayesian Choice Model for Eliminating Feedback Loops
Gökhan Çapan, Ilker Gündoğdu, Ali Caner Türkmen +2
Self-reinforcing feedback loops in personalization systems are typically caused by users choosing from a limited set of alternatives presented systematically based on previous choi…
GluonTS: Probabilistic Time Series Models in Python
Alexander Alexandrov, Konstantinos Benidis, Michael Bohlke-Schneider +10
We introduce Gluon Time Series (GluonTS, available at https://gluon-ts.mxnet.io), a library for deep-learning-based time series modeling. GluonTS simplifies the development of and…