Alternatives and similar repositories for fglib

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

• mbforbes / py-factorgraph
  Factor graphs and loopy belief propagation implemented in Python
  ☆194Updated 3 years ago
• tu-rbo / differentiable-particle-filters
  Source code and data for the paper "Differentiable Particle Filters: End-to-End Learning with Algorithmic Priors"
  ☆187Updated 2 years ago
• rdlester / pyfac
  Python implementation of Sum-Product for Factor Graphs
  ☆44Updated 9 years ago
• ilyakava / sumproduct
  Sum product algorithm - Belief propagation (message passing) for factor graphs
  ☆89Updated 7 years ago
• jstraub / dpMM
  Dirichlet Process Mixture Model sampling-based inference algorithms
  ☆14Updated 8 years ago
• jstraub / dpMMlowVar
  Bayesian nonparametric small-variance asymptotic clustering algorithms
  ☆20Updated 8 years ago
• ChristophJud / GPR
  Basic Gaussian process regression library. (Eigen3 required)
  ☆26Updated 10 years ago
• trevorcampbell / dynamic-means
  A clustering library for large/temporally evolving datasets
  ☆48Updated 8 years ago
• marionmari / pyGPs
  pyGPs is a library containing an object-oriented python implementation for Gaussian Process (GP) regression and classification.
  ☆217Updated 6 years ago
• krashkov / Belief-Propagation
  Overview and implementation of Belief Propagation and Loopy Belief Propagation algorithms: sum-product, max-product, max-sum
  ☆181Updated 6 years ago
• hoonose / robust-filter
  [ICML 2017] Robust estimation of mean and covariance in high dimensions
  ☆33Updated 5 years ago
• sailinglab / pgm-spring-2019
  Course webpage for PGM, Spring 2019.
  ☆76Updated 4 years ago
• zzhang1987 / Factor-Graph-Neural-Network
  Factor Graph Neural Network
  ☆76Updated 4 years ago
• SheffieldML / GPc
  Gaussian process code in C++ including some implementations of GP-LVM and IVM.
  ☆71Updated 4 years ago
• duvenaud / phd-thesis
  I am in [research] stepped in so far that, should I wade no more, Returning were as tedious as go o'er. -MacBeth
  ☆188Updated 11 years ago
• Jgmorton / vbf
  Implementation of Deep Variational Bayes Filter
  ☆12Updated 6 years ago
• boschresearch / PR-SSM
  Python implementation of the PR-SSM.
  ☆56Updated 7 years ago
• yunjhongwu / Sticky-HDPHMM-demo
  Sticky hierarchical Dirichlet process hidden Markov model for time series denoising
  ☆50Updated 9 years ago
• alshedivat / keras-gp
  Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.
  ☆251Updated last year
• clinicalml / structuredinference
  Structured Inference Networks for Nonlinear State Space Models
  ☆275Updated 8 years ago
• yaringal / DropoutUncertaintyDemos
  What My Deep Model Doesn't Know...
  ☆116Updated 10 years ago
• simonkamronn / kvae
  Kalman Variational Auto-Encoder
  ☆137Updated 6 years ago
• jmetzen / gp_extras
  Additional kernels that can be used with scikit-learn's Gaussian Process module
  ☆82Updated last year
• montrealrobotics / dal
  Repository for Deep Active Localization research and benchmarks
  ☆36Updated 5 years ago
• Yusufma03 / pfrnns
  Particle Filter Recurrent Neural Networks (AAAI 2020)
  ☆78Updated last year
• jmetzen / bayesian_optimization
  Bayesian optimization
  ☆38Updated 6 years ago
• paulorauber / pgm
  Probabilistic graphical models in python
  ☆24Updated 6 years ago
• anassinator / gp
  Differentiable Gaussian Process implementation for PyTorch
  ☆22Updated 7 years ago
• SkafteNicki / cuda_expm
  Matrix exponential in cuda for pytorch and tensorflow
  ☆17Updated 7 years ago
• numericalalgorithmsgroup / dfogn
  DFO-GN: Derivative-Free Optimization using Gauss-Newton
  ☆24Updated 2 years ago