Neural Symbolic Regression Boosts Network Dynamics Prediction Accuracy by Up to 60%

The Tsinghua team introduced ND², a neural‑symbolic regression that transforms high‑dimensional network search into a one‑dimensional problem using network dynamical operators and an NDformer‑guided symbolic search, achieving 60% higher accuracy on gene‑expression and ecological models and revealing cross‑scale epidemic dynamics.

Complex SystemsEpidemic ModelingNDformer

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Neural Symbolic Regression Boosts Network Dynamics Prediction Accuracy by Up to 60%

Model Perspective

May 26, 2024 · Fundamentals

Unlocking Complex Systems: How Agent-Based Modeling Simulates Traffic and Epidemics

This article introduces Agent-Based Modeling (ABM) as a powerful tool for simulating complex systems such as traffic congestion and disease spread, explains its core components, mathematical formulation, simulation steps, and provides a Python example of an epidemic model.

Agent-Based ModelingComplex SystemsComputational Modeling

0 likes · 8 min read

Unlocking Complex Systems: How Agent-Based Modeling Simulates Traffic and Epidemics

Model Perspective

May 26, 2022 · Fundamentals

How Do SI, SIS, and SIR Models Explain Epidemic Spread?

This article introduces exponential, SI, SIS, and SIR epidemic models, explains their assumptions, derives differential equations, and compares their predictions about infection dynamics and immunity.

Epidemic ModelingSI modelSIR model

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How Do SI, SIS, and SIR Models Explain Epidemic Spread?