Alternatives and similar repositories for APDOCC:

Users that are interested in APDOCC are comparing it to the libraries listed below

• ImperialCollegeLondon / RCDS-profiling-and-optimisation-in-python
  ☆32Updated 2 months ago
• ICB-DCM / pyPESTO
  python Parameter EStimation TOolbox
  ☆231Updated last week
• ziatdinovmax / gpax
  Gaussian Processes for Experimental Sciences
  ☆217Updated 3 months ago
• ICB-DCM / pyABC
  distributed, likelihood-free inference
  ☆207Updated 3 months ago
• DiffusionMapsAcademics / pyDiffMap
  Library for diffusion maps
  ☆46Updated 3 years ago
• zwicker-group / tutorial-pattern-formation-in-cells
  Tutorial on "Simulations of pattern formation in biological cells"
  ☆11Updated 4 months ago
• MichaelClerx / making-figures
  Tips on figure making, plus help with Inkscape and Matplotlib.
  ☆44Updated last year
• LRydin / KramersMoyal
  kramersmoyal: Kramers-Moyal coefficients for stochastic data of any dimension, to any desired order
  ☆69Updated last month
• eth-cscs / abcpy
  ABCpy package
  ☆113Updated 8 months ago
• DanielSank / vankampen-stochastic
  Exercises and notes for N.G. Van Kampen's Stochastic Processes in Physics and Chemistry
  ☆35Updated 3 months ago
• florisvb / PyNumDiff
  Methods for numerical differentiation of noisy data in python
  ☆113Updated last year
• AntonioCCosta / maximally_predictive_states
  Code for reproducing the results of the preprint Maximally Predictive Ensemble Dynamics from Data (2021)
  ☆13Updated 5 months ago
• ecotner / statistical-rethinking
  Following along with Statistical Rethinking text on Bayesian modeling by McElreath
  ☆53Updated 4 years ago
• matt-graham / mici
  Manifold Markov chain Monte Carlo methods in Python
  ☆226Updated last week
• pymc-devs / sunode
  Solve ODEs fast, with support for PyMC
  ☆112Updated 8 months ago
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆69Updated 4 years ago
• danhphan / workshops
  workshops
  ☆12Updated last year
• ICB-DCM / parPE
  Parameter estimation for dynamical models using high-performance computing, batch and mini-batch optimizers, and dynamic load balancing.
  ☆21Updated last month
• PrincetonUniversity / removing_tedium
  Linux productivity tools and practices for researchers
  ☆75Updated 2 months ago
• sbi-benchmark / sbibm
  Simulation-based inference benchmark
  ☆95Updated last week
• sissa-data-science / DADApy
  Distance-based Analysis of DAta-manifolds in python
  ☆116Updated 2 weeks ago
• amepproject / amep
  The Active Matter Evaluation Package (AMEP) - a Python library for the analysis of particle-based and continuum simulation data of soft a…
  ☆12Updated last month
• ColCarroll / minimc
  Just a little MCMC
  ☆219Updated 7 months ago
• pints-team / pints
  Probabilistic Inference on Noisy Time Series
  ☆230Updated 3 weeks ago
• andgoldschmidt / derivative
  Optimal numerical differentiation of noisy time series data in python.
  ☆59Updated 5 months ago
• peastman / statmech
  ☆124Updated 6 years ago
• Llewelyn62 / Non-linear-dynamics-Strogatz
  Python scripts connected to Strogatz's nonlinear dynamics and chaos theory text.
  ☆93Updated last year
• JaxGaussianProcesses / GPJax
  Gaussian processes in JAX.
  ☆474Updated 2 months ago
• simetenn / uncertainpy
  Uncertainpy: a Python toolbox for uncertainty quantification and sensitivity analysis, tailored towards computational neuroscience.
  ☆228Updated 2 years ago
• ronceray / StochasticForceInference
  Python implementation of the force and diffusion inference method described in (Frishman and Ronceray, Phys. Rev. X 10, 021009, 2020).
  ☆27Updated 2 years ago