Alternatives and similar repositories for LangevinMC

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

• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆86Updated 5 years ago
• gianlucadetommaso / Stein-variational-samplers
  Python and MATLAB code for Stein Variational sampling methods
  ☆27Updated 6 years ago
• benrhodes26 / tre_code
  ☆24Updated 4 years ago
• AWehenkel / UMNN
  Implementation of Unconstrained Monotonic Neural Network and the related experiments. These architectures are particularly useful for mod…
  ☆126Updated 2 months ago
• DartML / Stein-Variational-Gradient-Descent
  code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"
  ☆101Updated 6 years ago
• hughsalimbeni / bayesian_benchmarks
  A community repository for benchmarking Bayesian methods
  ☆112Updated 4 years ago
• matt-graham / mici
  Manifold Markov chain Monte Carlo methods in Python
  ☆236Updated last month
• gpapamak / maf
  Masked Autoregressive Flow
  ☆219Updated last year
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆32Updated 5 years ago
• akuhren / selective_gp
  Code accompanying the paper "Probabilistic Selection of Inducing Points in Sparse Gaussian Processes".
  ☆25Updated 3 years ago
• xwinxu / bayeSDE
  Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"
  ☆174Updated 4 years ago
• markvdw / RobustGP
  Robust initialisation of inducing points in sparse variational GP regression models.
  ☆34Updated 3 years ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆45Updated last year
• conormdurkan / lfi
  Neural likelihood-free methods in PyTorch.
  ☆39Updated 6 years ago
• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆54Updated 5 years ago
• blei-lab / variational-smc
  Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)
  ☆66Updated 6 years ago
• YannDubs / Neural-Process-Family
  Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.
  ☆228Updated last year
• BorealisAI / continuous-time-flow-process
  PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)
  ☆48Updated 5 years ago
• MFreidank / pysgmcmc
  Bayesian Deep Learning with Stochastic Gradient MCMC Methods
  ☆38Updated 4 years ago
• brain-research / nngp
  Deep neural network kernel for Gaussian process
  ☆212Updated 5 years ago
• UCL-SML / Doubly-Stochastic-DGP
  Deep Gaussian Processes with Doubly Stochastic Variational Inference
  ☆151Updated 6 years ago
• gpapamak / snl
  Sequential Neural Likelihood
  ☆42Updated 6 years ago
• ialong / GPt
  Gaussian Processes for Sequential Data
  ☆19Updated 5 years ago
• AVMCMC / AuxiliaryVariationalMCMC
  Code required to reproduce the experiments in Auxiliary Variational MCMC
  ☆17Updated 7 years ago
• freelunchtheorem / Conditional_Density_Estimation
  Python and torch-based package implementing various parametric and nonparametric methods for conditional density estimation
  ☆197Updated last month
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆83Updated last year
• dilinwang820 / Stein-Variational-Gradient-Descent
  code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"
  ☆417Updated last year
• alisiahkoohi / Langevin-dynamics
  Sampling with gradient-based Markov Chain Monte Carlo approaches
  ☆109Updated last year
• VincentStimper / resampled-base-flows
  Normalizing Flows with a resampled base distribution
  ☆47Updated 3 years ago
• secondmind-labs / GPflux
  Deep GPs built on top of TensorFlow/Keras and GPflow
  ☆128Updated last year