2 citations · 4 across the 4 of their papers we have counts for
4 papers
A Unified Particle Filter LSTM for Data-Driven Process Simulation
Parvin Malekzadeh, Opher Baron, Dmitry Krass
Data-driven process simulation aims to generate realistic case trajectories from historical event logs without requiring an explicitly specified model of the underlying dynamics. D…
Approximating G(t)/GI/1 queues with deep learning
Eliran Sherzer, Opher Baron, Dmitry Krass +1
In this paper, we apply a supervised machine-learning approach to solve a fundamental problem in queueing theory: estimating the transient distribution of the number in the system…
Can I Trust My Simulation Model? Measuring the Quality of Business Process Simulation Models
David Chapela-Campa, Ismail Benchekroun, Opher Baron +3
Business Process Simulation (BPS) is an approach to analyze the performance of business processes under different scenarios. For example, BPS allows us to estimate what would be th…
Can machines solve general queueing systems?
Eliran Sherzer, Arik Senderovich, Opher Baron +1
In this paper, we analyze how well a machine can solve a general problem in queueing theory. To answer this question, we use a deep learning model to predict the stationary queue-l…