eth-cscs / abcpy-models

Related projects ⓘ

Alternatives and complementary repositories for abcpy-models

• jajcayn / pygpso
  Gaussian-Processes Surrogate Optimisation in python
  ☆19Updated 3 years ago
• sremes / nonstationary-spectral-kernels
  Implementation for Non-stationary Spectral Kernels (NIPS 2017)
  ☆20Updated 4 years ago
• vr308 / Generalised-Gaussian-Processes
  Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods
  ☆21Updated last year
• aterenin / SparseGPAX
  An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.
  ☆22Updated 3 years ago
• bernarditaried / ZigZag-Sampling-Tutorial
  This tutorial is a basic guide to understanding the Zig-Zag Sampling method. This document is released with the aim of diffusion and shar…
  ☆18Updated 5 years ago
• AaltoPML / spatiotemporal-graph-kernels
  The official implementation of Non-separable Spatio-temporal Graph Kernels via SPDEs.
  ☆15Updated 2 years ago
• wesselb / mlkernels
  Kernels, the machine learning ones
  ☆14Updated last year
• abhiagwl / vistan
  A simple library to run variational inference on Stan models.
  ☆26Updated last year
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 5 years ago
• robsalomone / Deep-Probabilistic-Models-Course
  Deep Probabalistic Models: Materials for my course for the Australian Mathematical Sciences Institute (AMSI) Winter School 2021
  ☆10Updated 2 years ago
• mattiasvillani / BayesianLearningBook
  Home for the book-in-progress 'Bayesian Learning'
  ☆28Updated 2 months ago
• anastasiospanagiotelis / DimensionReduction
  Short course on dimension reduction for AMSI
  ☆36Updated last year
• Tom-Ryder / VIforSDEs
  A variational method for fast, approximate inference for stochastic differential equations.
  ☆43Updated 6 years ago
• keisuke198619 / GraphDMD
  Dynamic mode decomposition with dependent structure among observables (Graph DMD)
  ☆11Updated 4 years ago
• maziarraissi / ParametricGP
  Parametric Gaussian Process Regression for Big Data
  ☆44Updated 4 years ago
• martiningram / mcmc_runtime_comparison
  Compares Stan, PyMC, and PyMC + JAX numpyro sampler on a model for tennis
  ☆29Updated last year
• justindomke / pangolin
  probabilistic programming focused on fun
  ☆35Updated 2 weeks ago
• RajDandekar / MSML21_BayesianNODE
  ☆36Updated 2 years ago
• andykitchen / numpyo-examples
  Numpyro examples in Python notebooks
  ☆11Updated 4 years ago
• QuantEcon / lecture-jax
  Lectures on Quantitative Economics Using JAX
  ☆28Updated 2 weeks ago
• ThomasMBury / deep-early-warnings-pnas
  Repository to accompany the publication 'Deep learning for early warning signals of tipping points', PNAS (2021)
  ☆51Updated 2 years ago
• PredictiveIntelligenceLab / GP-NODEs
  ☆27Updated 2 years ago
• aterenin / SparseGaussianProcesses.jl
  A Julia implementation of sparse Gaussian processes via path-wise doubly stochastic variational inference.
  ☆33Updated 4 years ago
• gatsby-sahani / gp-sde
  ☆12Updated last year
• alpha-davidson / TensorBNN
  Full Bayesian inference for neural networks using TensorFlow
  ☆15Updated 3 years ago
• flatironinstitute / bayes-kit
  Bayesian inference and posterior analysis for Python
  ☆42Updated 10 months ago
• jgorham / SteinDiscrepancy.jl
  Practical tools for quantifying how well a sample approximates a target distribution
  ☆27Updated 4 years ago
• pnkraemer / tornadox
  Probabilistic ODE solvers are fun, but are they fast? See also: https://github.com/pnkraemer/probdiffeq for JAX code or https://github.c…
  ☆20Updated 3 months ago
• evdoxiataka / ipme
  An interactive visualization tool that transforms probabilistic programming models into an "Interactive Probabilistic Models Explorer".
  ☆24Updated 4 months ago
• wesselb / gpar
  Implementation of the Gaussian Process Autoregressive Regression Model
  ☆60Updated 3 years ago