dimitra-maoutsa/odes_for_sdes
Deterministic particle dynamics for simulating Fokker-Planck probability flows
This framework helps scientists and engineers simulate the probability distribution of systems that change randomly over time. You input the mathematical description of your system's random behavior (Stochastic Differential Equation) and get out a smooth, computationally efficient simulation of how the probability of system states evolves. This is for researchers and practitioners in fields like physics, finance, or biology who need to understand the underlying probability flows of complex dynamic systems.
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Use this if you need to simulate the temporal evolution of probability densities governed by Fokker-Planck equations, especially when you require smooth transient solutions and computational efficiency.
Not ideal if you are looking for a simple, off-the-shelf solver for basic differential equations without a focus on stochastic processes or their probability distributions.
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MIT
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Last pushed
Mar 07, 2023
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