Enhancing Diversity and Feasibility: Joint Population Synthesis from Multi-source Data Using Generative Models | ScienceToStartup | ScienceToStartup

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References (37)

[1]

Collaborative generative adversarial networks for fusing household travel survey and smart card data to generate heterogeneous activity schedules in urban digital twins

2025Huichang Lee, Prateek Bansal et al.

[2]

Optimization Algorithms in Generative AI for Enhanced GAN Stability and Performance

2025Reem Al Maawali, Amna AL-Shidi

[3]

Founder's Pitch

"A generative model leveraging multi-source data to create diverse, feasible synthetic populations for agent-based modeling in urban planning."

Generative Models•Score: 7•View PDF ↗

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Enhancing Diversity and Feasibility: Joint Population Synthesis from Multi-source Data Using Generative Models

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References (37)

Founder's Pitch

"A generative model leveraging multi-source data to create diverse, feasible synthetic populations for agent-based modeling in urban planning."

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Enhancing Diversity and Feasibility: Joint Population Synthesis from Multi-source Data Using Generative Models

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References (37)

Founder's Pitch

"A generative model leveraging multi-source data to create diverse, feasible synthetic populations for agent-based modeling in urban planning."

Commercial Viability Breakdown

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