Decomposing force fields as flows on graphs reconstructed from stochastic trajectories
Disentangling irreversible and reversible forces from random fluctuations is a challenging problem in the analysis of stochastic trajectories measured from realworld dynamical systems. We present an approach to approximate the dynamics of a stationary Langevin process as a discrete-state Markov proc...
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| Aineistotyyppi: | Conference item |
| Kieli: | English |
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Proceedings of Machine Learning Research
2024
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