Simulation Study
Simulation studies encompass the use of computational models to investigate complex systems and processes across diverse scientific domains. Current research emphasizes developing sophisticated models, including deep neural networks, agent-based models, and generative models, to enhance realism, efficiency, and the ability to handle large-scale datasets. These studies are crucial for testing hypotheses, optimizing designs, and predicting outcomes in scenarios ranging from weather forecasting and traffic flow to robotic control and drug discovery, ultimately advancing scientific understanding and informing practical applications. The increasing integration of large language models further expands the scope and accessibility of simulation studies.
Papers
OysterNet: Enhanced Oyster Detection Using Simulation
Xiaomin Lin, Nitin J. Sanket, Nare Karapetyan, Yiannis Aloimonos
Sales Channel Optimization via Simulations Based on Observational Data with Delayed Rewards: A Case Study at LinkedIn
Diana M. Negoescu, Pasha Khosravi, Shadow Zhao, Nanyu Chen, Parvez Ahammad, Humberto Gonzalez