Physics-based ML for modelling stochastic reaction networks
- United States of America
- https://physics-based-ml.github.io
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- DyBoltzReducedModelsPaper
DyBoltzReducedModelsPaper PublicForked fromsmrfeld/DyBoltzReducedModelsPaper
Code for paper: J. Chem. Phys. 149, 034107 (2018) (arXiv:1803.01063)
Mathematica 1
- physics-based-ml-reaction-networks
physics-based-ml-reaction-networks PublicForked fromsmrfeld/physics-based-ml-reaction-networks
Code for paper "Physics-based machine learning for modeling IP3 induced calcium oscillations" - DOI: 10.5281/zenodo.4839127
Mathematica 1
- DynamicBoltzmannPaper
DynamicBoltzmannPaper PublicForked fromsmrfeld/DynamicBoltzmannPaper
Code used in arXiv:1808.08630
Mathematica
- ReducedLotkaVolterra
ReducedLotkaVolterra PublicForked fromsmrfeld/ReducedLotkaVolterra
Code used in paper "Deep Learning Moment Closure Approximations using Dynamic Boltzmann Distributions" arXiv 1905.12122
Mathematica
- gillespie-cpp
gillespie-cpp PublicForked fromsmrfeld/gillespie-cpp
Simple as it gets Gillespie library in C++, as a stepping stone for your own Gillespie codes
Mathematica
- LatticeGillespieCpp
LatticeGillespieCpp PublicForked fromsmrfeld/LatticeGillespieCpp
Gillespie Codes on Lattices in C++
Mathematica
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physics-based-ml/physics-based-ml.github.io’s past year of commit activity - LatticeGillespieCpp Public Forked fromsmrfeld/LatticeGillespieCpp
Gillespie Codes on Lattices in C++
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physics-based-ml/LatticeGillespieCpp’s past year of commit activity - gillespie-cpp Public Forked fromsmrfeld/gillespie-cpp
Simple as it gets Gillespie library in C++, as a stepping stone for your own Gillespie codes
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physics-based-ml/gillespie-cpp’s past year of commit activity - DyBoltzReducedModelsPaper Public Forked fromsmrfeld/DyBoltzReducedModelsPaper
Code for paper: J. Chem. Phys. 149, 034107 (2018) (arXiv:1803.01063)
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physics-based-ml/DyBoltzReducedModelsPaper’s past year of commit activity - ReducedLotkaVolterra Public Forked fromsmrfeld/ReducedLotkaVolterra
Code used in paper "Deep Learning Moment Closure Approximations using Dynamic Boltzmann Distributions" arXiv 1905.12122
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physics-based-ml/DynamicBoltzmannPaper’s past year of commit activity - DynamicBoltzmann Public Forked fromsmrfeld/DynamicBoltzmann
Dynamic Boltzmann Machine for Lattice Chemical Kinetics
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physics-based-ml/DynamicBoltzmann’s past year of commit activity - physics-based-ml-reaction-networks Public Forked fromsmrfeld/physics-based-ml-reaction-networks
Code for paper "Physics-based machine learning for modeling IP3 induced calcium oscillations" - DOI: 10.5281/zenodo.4839127
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physics-based-ml/physics-based-ml-reaction-networks’s past year of commit activity - sample-pairs-gaussian Public Forked fromsmrfeld/sample-pairs-gaussian
Python code to sample pairs of a given set of particles in n dims, where the probability for each pair is Gaussian
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physics-based-ml/sample-pairs-gaussian’s past year of commit activity
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