Data-driven Effective Modeling of Stochastic Chemical Reaction Networks

arXiv:2608.25421 · math.NA, cs.LG, cs.NA, math.DS · Submitted 2026-08-26 · Read on arXiv

math.NA, cs.LG, cs.NA, math.DS

Submitted: 2026-08-26

Updated: 2026-08-26

Terminology

• Normalizing Flow — 16× in this paper · explained in 3 episodes
• Accuracy — 11× in this paper · explained in 1 episode
• Generative Model — 6× in this paper · explained in 2 episodes
• Stochastic Simulation Algorithm — 5× in this paper
• Generative Models — 4× in this paper · explained in 2 episodes
• Normalizing Flows — 4× in this paper · explained in 4 episodes
• Abstraction — 3× in this paper · explained in 1 episode
• Chemical Master Equation — 3× in this paper
• DeepONet — 3× in this paper · explained in 2 episodes
• Stochastic Dynamics — 2× in this paper · explained in 2 episodes
• Activation Function — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Computational Biology — 1× in this paper · explained in 2 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Diffusion Processes — 1× in this paper · explained in 2 episodes
• Digital Twin — 1× in this paper · explained in 4 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Inverse Problem — 1× in this paper · explained in 2 episodes
• Physical Constraints — 1× in this paper · explained in 7 episodes
• Signal Temporal Logic (STL) — 1× in this paper · explained in 4 episodes
• Uncertainty Quantification — 1× in this paper · explained in 8 episodes

Sources

• Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems

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