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zipkinlab / DiRenzo_etal_2019_EcolAndEvol

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DiRenzo G. V., Che‐Castaldo C., Saunders S. P., Campbell Grant E. H., Zipkin E. F. 2019. Disease‐structured N‐mixture models: A practical guide to model disease dynamics using count data. Ecology and Evolution 9: 899–909.

bayesian hierarchical-models occupancy-model disease-ecology dail-madsen-model emerging-infectious-diseases generalized-n-mixture-model host-pathogen-interaction mark-recapture-models multistate-models
  • Updated Dec 3, 2019
  • HTML

igopalakrishna / sbsim

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Google Open-Source Project: Stochastic building simulator and real-world dataset for training and benchmarking reinforcement learning agents in energy-efficient smart control environments. Built with Gym, TensorFlow Agents, and 6+ years of real building data.

python docker reinforcement-learning openai-gym dataset energy-efficiency gym-environment smart-building occupancy-model smart-control building-simulation tensorflow-agents offline-rl climate-tech rl-benchmark
  • Updated Jul 27, 2025
  • Python

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