Alternatives and similar repositories for tdistfit:

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

• rmgarnett / gpml_extensions
  Provides various extensions to the GPML toolbox for Gaussian process inference in MATLAB.
  ☆31Updated 8 years ago
• PredictiveScienceLab / inverse-bgo
  Use Bayesian Global Optimization to solve inverse problems
  ☆13Updated 9 years ago
• gpstuff-dev / gpstuff
  GPstuff - Gaussian process models for Bayesian analysis
  ☆173Updated 2 years ago
• horchler / SDETools
  Matlab Toolbox for the Numerical Solution of Stochastic Differential Equations
  ☆101Updated 4 years ago
• jakeret / abcpmc
  Approximate Bayesian Computation Population Monte Carlo
  ☆41Updated 5 years ago
• mfouesneau / NUTS
  python version of the No-U-Turn Sampler (NUTS) from Hoffman & Gelman, 2011
  ☆127Updated 4 years ago
• AaltoML / hilbert-gp
  Codes for Hilbert space reduced-rank GP regression
  ☆14Updated 5 years ago
• kpchamp / MultiscaleDiscovery
  ☆27Updated 6 years ago
• shimazaki / AdaptiveKDE
  Python module for adaptive kernel density estimation
  ☆61Updated last year
• drrelyea / spgl1
  Port of SPGL1 to python
  ☆45Updated 7 months ago
• erichson / optht
  Optimal Hard Threshold for Matrix Denoising
  ☆37Updated 3 years ago
• pygpc-polynomial-chaos / pygpc
  A Sensitivity and uncertainty analysis toolbox for Python based on the generalized polynomial chaos method
  ☆80Updated last month
• kb-press / ndsplines
  Multi-dimensional B-splines
  ☆31Updated last week
• DrugowitschLab / VBLinLogit
  Variational Bayes linear and logistic regression
  ☆34Updated 5 years ago
• SimonDu / CUR-matrix-decomposition
  A matlab library for CUR matrix decomposition
  ☆26Updated 7 years ago
• stephenbeckr / zeroSR1
  Proximal gradient algorithm for convex optimization, using a diagonal +/- rank-1 norm
  ☆20Updated 3 months ago
• CivML-PolyMtl / OpenBDLM
  Bayesian Dynamic Linear Models for time-series analysis
  ☆26Updated 3 years ago
• dflemin3 / approxposterior
  A Python package for approximate Bayesian inference and optimization using Gaussian processes
  ☆42Updated last year
• Sohl-Dickstein / LAHMC
  Look Ahead Hamiltonian Monte Carlo
  ☆30Updated 10 years ago
• matt-graham / mici
  Manifold Markov chain Monte Carlo methods in Python
  ☆227Updated 2 months ago
• rmcgibbo / pyhmc
  Hamiltonain Monte Carlo in Python
  ☆39Updated 5 years ago
• aki-nishimura / NUTS-matlab
  ☆15Updated 8 years ago
• OxfordML / GPz
  GPz 2.0: Heteroscedastic Gaussian processes for uncertain and incomplete data
  ☆49Updated 3 years ago
• aaren / sparse_dmd
  sparse dynamic mode decomposition in python
  ☆37Updated 9 years ago
• maziarraissi / ParametricGP
  Parametric Gaussian Process Regression for Big Data
  ☆44Updated 5 years ago
• n-takeishi / bayesiandmd
  Bayesian Dynamic Mode Decomposition (Bayesian DMD)
  ☆18Updated 3 years ago
• erichson / DMDpack
  Dynamic Mode Decomposition
  ☆58Updated 7 years ago
• acerbilab / vbmc
  Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference in MATLAB
  ☆222Updated last year
• duvenaud / harlemcmc-shake
  Code to produce demos of Metroplis-Hastings and Hamiltonian Monte Carlo samplers.
  ☆37Updated 11 years ago
• narayanps / NolinearTimeSeriesAnalysis
  The codes in the toolbox can be used to perform nonlinear time series analysis on single(or multi) channel data. This is done by mapping …
  ☆31Updated 3 years ago