NIM: Modeling and Generation of Simulation Inputs via Generative Neural Network
Published in Winter Simulation Conference, 2020
🎉🎉🎉 Nominated as Finalist for Best Contributed Theoretical Paper
Description: We developed Neural Input Modeling (NIM), a novel framework to model and generate simulation input processes using Generative Neural Networks. This makes input modeling easier for both simulation novice and experts.
Website: Neural Input Modeling
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